Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born

PubMed Central

2012-01-01

We present an implementation of generalized Born implicit solvent all-atom classical molecular dynamics (MD) within the AMBER program package that runs entirely on CUDA enabled NVIDIA graphics processing units (GPUs). We discuss the algorithms that are used to exploit the processing power of the GPUs and show the performance that can be achieved in comparison to simulations on conventional CPU clusters. The implementation supports three different precision models in which the contributions to the forces are calculated in single precision floating point arithmetic but accumulated in double precision (SPDP), or everything is computed in single precision (SPSP) or double precision (DPDP). In addition to performance, we have focused on understanding the implications of the different precision models on the outcome of implicit solvent MD simulations. We show results for a range of tests including the accuracy of single point force evaluations and energy conservation as well as structural properties pertainining to protein dynamics. The numerical noise due to rounding errors within the SPSP precision model is sufficiently large to lead to an accumulation of errors which can result in unphysical trajectories for long time scale simulations. We recommend the use of the mixed-precision SPDP model since the numerical results obtained are comparable with those of the full double precision DPDP model and the reference double precision CPU implementation but at significantly reduced computational cost. Our implementation provides performance for GB simulations on a single desktop that is on par with, and in some cases exceeds, that of traditional supercomputers. PMID:22582031

A Fatty Acid Based Bayesian Approach for Inferring Diet in Aquatic Consumers

PubMed Central

Holtgrieve, Gordon W.; Ward, Eric J.; Ballantyne, Ashley P.; Burns, Carolyn W.; Kainz, Martin J.; Müller-Navarra, Doerthe C.; Persson, Jonas; Ravet, Joseph L.; Strandberg, Ursula; Taipale, Sami J.; Alhgren, Gunnel

2015-01-01

We modified the stable isotope mixing model MixSIR to infer primary producer contributions to consumer diets based on their fatty acid composition. To parameterize the algorithm, we generated a ‘consumer-resource library’ of FA signatures of Daphnia fed different algal diets, using 34 feeding trials representing diverse phytoplankton lineages. This library corresponds to the resource or producer file in classic Bayesian mixing models such as MixSIR or SIAR. Because this library is based on the FA profiles of zooplankton consuming known diets, and not the FA profiles of algae directly, trophic modification of consumer lipids is directly accounted for. To test the model, we simulated hypothetical Daphnia comprised of 80% diatoms, 10% green algae, and 10% cryptophytes and compared the FA signatures of these known pseudo-mixtures to outputs generated by the mixing model. The algorithm inferred these simulated consumers were comprised of 82% (63-92%) [median (2.5th to 97.5th percentile credible interval)] diatoms, 11% (4-22%) green algae, and 6% (0-25%) cryptophytes. We used the same model with published phytoplankton stable isotope (SI) data for δ13C and δ15N to examine how a SI based approach resolved a similar scenario. With SI, the algorithm inferred that the simulated consumer assimilated 52% (4-91%) diatoms, 23% (1-78%) green algae, and 18% (1-73%) cyanobacteria. The accuracy and precision of SI based estimates was extremely sensitive to both resource and consumer uncertainty, as well as the trophic fractionation assumption. These results indicate that when using only two tracers with substantial uncertainty for the putative resources, as is often the case in this class of analyses, the underdetermined constraint in consumer-resource SI analyses may be intractable. The FA based approach alleviated the underdetermined constraint because many more FA biomarkers were utilized (n < 20), different primary producers (e.g., diatoms, green algae, and cryptophytes) have very characteristic FA compositions, and the FA profiles of many aquatic primary consumers are strongly influenced by their diets. PMID:26114945

Evaluating the utility of syndromic surveillance algorithms for screening to detect potentially clonal hospital infection outbreaks

PubMed Central

Talbot, Thomas R; Schaffner, William; Bloch, Karen C; Daniels, Titus L; Miller, Randolph A

2011-01-01

Objective The authors evaluated algorithms commonly used in syndromic surveillance for use as screening tools to detect potentially clonal outbreaks for review by infection control practitioners. Design Study phase 1 applied four aberrancy detection algorithms (CUSUM, EWMA, space-time scan statistic, and WSARE) to retrospective microbiologic culture data, producing a list of past candidate outbreak clusters. In phase 2, four infectious disease physicians categorized the phase 1 algorithm-identified clusters to ascertain algorithm performance. In phase 3, project members combined the algorithms to create a unified screening system and conducted a retrospective pilot evaluation. Measurements The study calculated recall and precision for each algorithm, and created precision-recall curves for various methods of combining the algorithms into a unified screening tool. Results Individual algorithm recall and precision ranged from 0.21 to 0.31 and from 0.053 to 0.29, respectively. Few candidate outbreak clusters were identified by more than one algorithm. The best method of combining the algorithms yielded an area under the precision-recall curve of 0.553. The phase 3 combined system detected all infection control-confirmed outbreaks during the retrospective evaluation period. Limitations Lack of phase 2 reviewers' agreement indicates that subjective expert review was an imperfect gold standard. Less conservative filtering of culture results and alternate parameter selection for each algorithm might have improved algorithm performance. Conclusion Hospital outbreak detection presents different challenges than traditional syndromic surveillance. Nevertheless, algorithms developed for syndromic surveillance have potential to form the basis of a combined system that might perform clinically useful hospital outbreak screening. PMID:21606134

Design and algorithm research of high precision airborne infrared touch screen

NASA Astrophysics Data System (ADS)

Zhang, Xiao-Bing; Wang, Shuang-Jie; Fu, Yan; Chen, Zhao-Quan

2016-10-01

There are shortcomings of low precision, touch shaking, and sharp decrease of touch precision when emitting and receiving tubes are failure in the infrared touch screen. A high precision positioning algorithm based on extended axis is proposed to solve these problems. First, the unimpeded state of the beam between emitting and receiving tubes is recorded as 0, while the impeded state is recorded as 1. Then, the method of oblique scan is used, in which the light of one emitting tube is used for five receiving tubes. The impeded information of all emitting and receiving tubes is collected as matrix. Finally, according to the method of arithmetic average, the position of the touch object is calculated. The extended axis positioning algorithm is characteristic of high precision in case of failure of individual infrared tube and affects slightly the precision. The experimental result shows that the 90% display area of the touch error is less than 0.25D, where D is the distance between adjacent emitting tubes. The conclusion is gained that the algorithm based on extended axis has advantages of high precision, little impact when individual infrared tube is failure, and using easily.

GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems.

PubMed

Sadowski, Krzysztof L; Thierens, Dirk; Bosman, Peter A N

2018-01-01

Learning and exploiting problem structure is one of the key challenges in optimization. This is especially important for black-box optimization (BBO) where prior structural knowledge of a problem is not available. Existing model-based Evolutionary Algorithms (EAs) are very efficient at learning structure in both the discrete, and in the continuous domain. In this article, discrete and continuous model-building mechanisms are integrated for the Mixed-Integer (MI) domain, comprising discrete and continuous variables. We revisit a recently introduced model-based evolutionary algorithm for the MI domain, the Genetic Algorithm for Model-Based mixed-Integer opTimization (GAMBIT). We extend GAMBIT with a parameterless scheme that allows for practical use of the algorithm without the need to explicitly specify any parameters. We furthermore contrast GAMBIT with other model-based alternatives. The ultimate goal of processing mixed dependences explicitly in GAMBIT is also addressed by introducing a new mechanism for the explicit exploitation of mixed dependences. We find that processing mixed dependences with this novel mechanism allows for more efficient optimization. We further contrast the parameterless GAMBIT with Mixed-Integer Evolution Strategies (MIES) and other state-of-the-art MI optimization algorithms from the General Algebraic Modeling System (GAMS) commercial algorithm suite on problems with and without constraints, and show that GAMBIT is capable of solving problems where variable dependences prevent many algorithms from successfully optimizing them.

Study on distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng

2017-06-01

Integration of distributed heterogeneous data sources is the key issues under the big data applications. In this paper the strategy of variable precision is introduced to the concept lattice, and the one-to-one mapping mode of variable precision concept lattice and ontology concept lattice is constructed to produce the local ontology by constructing the variable precision concept lattice for each subsystem, and the distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database is proposed to draw support from the special relationship between concept lattice and ontology construction. Finally, based on the standard of main concept lattice of the existing heterogeneous database generated, a case study has been carried out in order to testify the feasibility and validity of this algorithm, and the differences between the main concept lattice and the standard concept lattice are compared. Analysis results show that this algorithm above-mentioned can automatically process the construction process of distributed concept lattice under the heterogeneous data sources.

Least-dependent-component analysis based on mutual information

NASA Astrophysics Data System (ADS)

Stögbauer, Harald; Kraskov, Alexander; Astakhov, Sergey A.; Grassberger, Peter

2004-12-01

We propose to use precise estimators of mutual information (MI) to find the least dependent components in a linearly mixed signal. On the one hand, this seems to lead to better blind source separation than with any other presently available algorithm. On the other hand, it has the advantage, compared to other implementations of “independent” component analysis (ICA), some of which are based on crude approximations for MI, that the numerical values of the MI can be used for (i) estimating residual dependencies between the output components; (ii) estimating the reliability of the output by comparing the pairwise MIs with those of remixed components; and (iii) clustering the output according to the residual interdependencies. For the MI estimator, we use a recently proposed k -nearest-neighbor-based algorithm. For time sequences, we combine this with delay embedding, in order to take into account nontrivial time correlations. After several tests with artificial data, we apply the resulting MILCA (mutual-information-based least dependent component analysis) algorithm to a real-world dataset, the ECG of a pregnant woman.

An improved NSGA - II algorithm for mixed model assembly line balancing

NASA Astrophysics Data System (ADS)

Wu, Yongming; Xu, Yanxia; Luo, Lifei; Zhang, Han; Zhao, Xudong

2018-05-01

Aiming at the problems of assembly line balancing and path optimization for material vehicles in mixed model manufacturing system, a multi-objective mixed model assembly line (MMAL), which is based on optimization objectives, influencing factors and constraints, is established. According to the specific situation, an improved NSGA-II algorithm based on ecological evolution strategy is designed. An environment self-detecting operator, which is used to detect whether the environment changes, is adopted in the algorithm. Finally, the effectiveness of proposed model and algorithm is verified by examples in a concrete mixing system.

Determining the biomass fraction of mixed waste fuels: A comparison of existing industry and {sup 14}C-based methodologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muir, G.K.P., E-mail: Graham.Muir@glasgow.ac.uk; Hayward, S.; Tripney, B.G.

2015-01-15

Highlights: • Compares industry standard and {sup 14}C methods for determining bioenergy content of MSW. • Differences quantified through study at an operational energy from waste plant. • Manual sort and selective dissolution are unreliable measures of feedstock bioenergy. • {sup 14}C methods (esp. AMS) improve precision and reliability of bioenergy determination. • Implications for electricity generators and regulators for award of bio-incentives. - Abstract: {sup 14}C analysis of flue gas by accelerator mass spectrometry (AMS) and liquid scintillation counting (LSC) were used to determine the biomass fraction of mixed waste at an operational energy-from-waste (EfW) plant. Results were convertedmore » to bioenergy (% total) using mathematical algorithms and assessed against existing industry methodologies which involve manual sorting and selective dissolution (SD) of feedstock. Simultaneous determinations using flue gas showed excellent agreement: 44.8 ± 2.7% for AMS and 44.6 ± 12.3% for LSC. Comparable bioenergy results were obtained using a feedstock manual sort procedure (41.4%), whilst a procedure based on selective dissolution of representative waste material is reported as 75.5% (no errors quoted). {sup 14}C techniques present significant advantages in data acquisition, precision and reliability for both electricity generator and industry regulator.« less

Snow depth and snow cover retrieval from FengYun3B microwave radiation imagery based on a snow passive microwave unmixing method in Northeast China

NASA Astrophysics Data System (ADS)

Gu, Lingjia; Ren, Ruizhi; Zhao, Kai; Li, Xiaofeng

2014-01-01

The precision of snow parameter retrieval is unsatisfactory for current practical demands. The primary reason is because of the problem of mixed pixels that are caused by low spatial resolution of satellite passive microwave data. A snow passive microwave unmixing method is proposed in this paper, based on land cover type data and the antenna gain function of passive microwaves. The land cover type of Northeast China is partitioned into grass, farmland, bare soil, forest, and water body types. The component brightness temperatures (CBT), namely unmixed data, with 1 km data resolution are obtained using the proposed unmixing method. The snow depth determined by the CBT and three snow depth retrieval algorithms are validated through field measurements taken in forest and farmland areas of Northeast China in January 2012 and 2013. The results show that the overall of the retrieval precision of the snow depth is improved by 17% in farmland areas and 10% in forest areas when using the CBT in comparison with the mixed pixels. The snow cover results based on the CBT are compared with existing MODIS snow cover products. The results demonstrate that more snow cover information can be obtained with up to 86% accuracy.

Abbreviation definition identification based on automatic precision estimates.

PubMed

Sohn, Sunghwan; Comeau, Donald C; Kim, Won; Wilbur, W John

2008-09-25

The rapid growth of biomedical literature presents challenges for automatic text processing, and one of the challenges is abbreviation identification. The presence of unrecognized abbreviations in text hinders indexing algorithms and adversely affects information retrieval and extraction. Automatic abbreviation definition identification can help resolve these issues. However, abbreviations and their definitions identified by an automatic process are of uncertain validity. Due to the size of databases such as MEDLINE only a small fraction of abbreviation-definition pairs can be examined manually. An automatic way to estimate the accuracy of abbreviation-definition pairs extracted from text is needed. In this paper we propose an abbreviation definition identification algorithm that employs a variety of strategies to identify the most probable abbreviation definition. In addition our algorithm produces an accuracy estimate, pseudo-precision, for each strategy without using a human-judged gold standard. The pseudo-precisions determine the order in which the algorithm applies the strategies in seeking to identify the definition of an abbreviation. On the Medstract corpus our algorithm produced 97% precision and 85% recall which is higher than previously reported results. We also annotated 1250 randomly selected MEDLINE records as a gold standard. On this set we achieved 96.5% precision and 83.2% recall. This compares favourably with the well known Schwartz and Hearst algorithm. We developed an algorithm for abbreviation identification that uses a variety of strategies to identify the most probable definition for an abbreviation and also produces an estimated accuracy of the result. This process is purely automatic.

Delivery confirmation of bolus electron conformal therapy combined with intensity modulated x-ray therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kavanaugh, James A.; Hogstrom, Kenneth R.; Fontenot, Jonas P.

2013-02-15

Purpose: The purpose of this study was to demonstrate that a bolus electron conformal therapy (ECT) dose plan and a mixed beam plan, composed of an intensity modulated x-ray therapy (IMXT) dose plan optimized on top of the bolus ECT plan, can be accurately delivered. Methods: Calculated dose distributions were compared with measured dose distributions for parotid and chest wall (CW) bolus ECT and mixed beam plans, each simulated in a cylindrical polystyrene phantom that allowed film dose measurements. Bolus ECT plans were created for both parotid and CW PTVs (planning target volumes) using 20 and 16 MeV beams, respectively,more » whose 90% dose surface conformed to the PTV. Mixed beam plans consisted of an IMXT dose plan optimized on top of the bolus ECT dose plan. The bolus ECT, IMXT, and mixed beam dose distributions were measured using radiographic films in five transverse and one sagittal planes for a total of 36 measurement conditions. Corrections for film dose response, effects of edge-on photon irradiation, and effects of irregular phantom optical properties on the Cerenkov component of the film signal resulted in high precision measurements. Data set consistency was verified by agreement of depth dose at the intersections of the sagittal plane with the five measured transverse planes. For these same depth doses, results for the mixed beam plan agreed with the sum of the individual depth doses for the bolus ECT and IMXT plans. The six mean measured planar dose distributions were compared with those calculated by the treatment planning system for all modalities. Dose agreement was assessed using the 4% dose difference and 0.2 cm distance to agreement. Results: For the combined high-dose region and low-dose region, pass rates for the parotid and CW plans were 98.7% and 96.2%, respectively, for the bolus ECT plans and 97.9% and 97.4%, respectively, for the mixed beam plans. For the high-dose gradient region, pass rates for the parotid and CW plans were 93.1% and 94.62%, respectively, for the bolus ECT plans and 89.2% and 95.1%, respectively, for the mixed beam plans. For all regions, pass rates for the parotid and CW plans were 98.8% and 97.3%, respectively, for the bolus ECT plans and 97.5% and 95.9%, respectively, for the mixed beam plans. For the IMXT component of the mixed beam plans, pass rates for the parotid and CW plans were 93.7% and 95.8%. Conclusions: Bolus ECT and mixed beam therapy dose delivery to the phantom were more accurate than IMXT delivery, adding confidence to the use of planning, fabrication, and delivery for bolus ECT tools either alone or as part of mixed beam therapy. The methodology reported in this work could serve as a basis for future standardization of the commissioning of bolus ECT or mixed beam therapy. When applying this technology to patients, it is recommended that an electron dose algorithm more accurate than the pencil beam algorithm, e.g., a Monte Carlo algorithm or analytical transport such as the pencil beam redefinition algorithm, be used for planning to ensure the desired accuracy.« less

Maximum likelihood estimates, from censored data, for mixed-Weibull distributions

NASA Astrophysics Data System (ADS)

Jiang, Siyuan; Kececioglu, Dimitri

1992-06-01

A new algorithm for estimating the parameters of mixed-Weibull distributions from censored data is presented. The algorithm follows the principle of maximum likelihood estimate (MLE) through the expectation and maximization (EM) algorithm, and it is derived for both postmortem and nonpostmortem time-to-failure data. It is concluded that the concept of the EM algorithm is easy to understand and apply (only elementary statistics and calculus are required). The log-likelihood function cannot decrease after an EM sequence; this important feature was observed in all of the numerical calculations. The MLEs of the nonpostmortem data were obtained successfully for mixed-Weibull distributions with up to 14 parameters in a 5-subpopulation, mixed-Weibull distribution. Numerical examples indicate that some of the log-likelihood functions of the mixed-Weibull distributions have multiple local maxima; therefore, the algorithm should start at several initial guesses of the parameter set.

Precise locating approach of the beacon based on gray gradient segmentation interpolation in satellite optical communications.

PubMed

Wang, Qiang; Liu, Yuefei; Chen, Yiqiang; Ma, Jing; Tan, Liying; Yu, Siyuan

2017-03-01

Accurate location computation for a beacon is an important factor of the reliability of satellite optical communications. However, location precision is generally limited by the resolution of CCD. How to improve the location precision of a beacon is an important and urgent issue. In this paper, we present two precise centroid computation methods for locating a beacon in satellite optical communications. First, in terms of its characteristics, the beacon is divided into several parts according to the gray gradients. Afterward, different numbers of interpolation points and different interpolation methods are applied in the interpolation area; we calculate the centroid position after interpolation and choose the best strategy according to the algorithm. The method is called a "gradient segmentation interpolation approach," or simply, a GSI (gradient segmentation interpolation) algorithm. To take full advantage of the pixels of the beacon's central portion, we also present an improved segmentation square weighting (SSW) algorithm, whose effectiveness is verified by the simulation experiment. Finally, an experiment is established to verify GSI and SSW algorithms. The results indicate that GSI and SSW algorithms can improve locating accuracy over that calculated by a traditional gray centroid method. These approaches help to greatly improve the location precision for a beacon in satellite optical communications.

Validating precision estimates in horizontal wind measurements from a Doppler lidar

DOE PAGES

Newsom, Rob K.; Brewer, W. Alan; Wilczak, James M.; ...

2017-03-30

Results from a recent field campaign are used to assess the accuracy of wind speed and direction precision estimates produced by a Doppler lidar wind retrieval algorithm. The algorithm, which is based on the traditional velocity-azimuth-display (VAD) technique, estimates the wind speed and direction measurement precision using standard error propagation techniques, assuming the input data (i.e., radial velocities) to be contaminated by random, zero-mean, errors. For this study, the lidar was configured to execute an 8-beam plan-position-indicator (PPI) scan once every 12 min during the 6-week deployment period. Several wind retrieval trials were conducted using different schemes for estimating themore » precision in the radial velocity measurements. Here, the resulting wind speed and direction precision estimates were compared to differences in wind speed and direction between the VAD algorithm and sonic anemometer measurements taken on a nearby 300 m tower.« less

LDPC decoder with a limited-precision FPGA-based floating-point multiplication coprocessor

NASA Astrophysics Data System (ADS)

Moberly, Raymond; O'Sullivan, Michael; Waheed, Khurram

2007-09-01

Implementing the sum-product algorithm, in an FPGA with an embedded processor, invites us to consider a tradeoff between computational precision and computational speed. The algorithm, known outside of the signal processing community as Pearl's belief propagation, is used for iterative soft-decision decoding of LDPC codes. We determined the feasibility of a coprocessor that will perform product computations. Our FPGA-based coprocessor (design) performs computer algebra with significantly less precision than the standard (e.g. integer, floating-point) operations of general purpose processors. Using synthesis, targeting a 3,168 LUT Xilinx FPGA, we show that key components of a decoder are feasible and that the full single-precision decoder could be constructed using a larger part. Soft-decision decoding by the iterative belief propagation algorithm is impacted both positively and negatively by a reduction in the precision of the computation. Reducing precision reduces the coding gain, but the limited-precision computation can operate faster. A proposed solution offers custom logic to perform computations with less precision, yet uses the floating-point format to interface with the software. Simulation results show the achievable coding gain. Synthesis results help theorize the the full capacity and performance of an FPGA-based coprocessor.

Mapped Landmark Algorithm for Precision Landing

NASA Technical Reports Server (NTRS)

Johnson, Andrew; Ansar, Adnan; Matthies, Larry

2007-01-01

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

A survey of telerobotic surface finishing

NASA Astrophysics Data System (ADS)

Höglund, Thomas; Alander, Jarmo; Mantere, Timo

2018-05-01

This is a survey of research published on the subjects of telerobotics, haptic feedback, and mixed reality applied to surface finishing. The survey especially focuses on how visuo-haptic feedback can be used to improve a grinding process using a remote manipulator or robot. The benefits of teleoperation and reasons for using haptic feedback are presented. The use of genetic algorithms for optimizing haptic sensing is briefly discussed. Ways of augmenting the operator's vision are described. Visual feedback can be used to find defects and analyze the quality of the surface resulting from the surface finishing process. Visual cues can also be used to aid a human operator in manipulating a robot precisely and avoiding collisions.

Fully accelerating quantum Monte Carlo simulations of real materials on GPU clusters

NASA Astrophysics Data System (ADS)

Esler, Kenneth

2011-03-01

Quantum Monte Carlo (QMC) has proved to be an invaluable tool for predicting the properties of matter from fundamental principles, combining very high accuracy with extreme parallel scalability. By solving the many-body Schrödinger equation through a stochastic projection, it achieves greater accuracy than mean-field methods and better scaling with system size than quantum chemical methods, enabling scientific discovery across a broad spectrum of disciplines. In recent years, graphics processing units (GPUs) have provided a high-performance and low-cost new approach to scientific computing, and GPU-based supercomputers are now among the fastest in the world. The multiple forms of parallelism afforded by QMC algorithms make the method an ideal candidate for acceleration in the many-core paradigm. We present the results of porting the QMCPACK code to run on GPU clusters using the NVIDIA CUDA platform. Using mixed precision on GPUs and MPI for intercommunication, we observe typical full-application speedups of approximately 10x to 15x relative to quad-core CPUs alone, while reproducing the double-precision CPU results within statistical error. We discuss the algorithm modifications necessary to achieve good performance on this heterogeneous architecture and present the results of applying our code to molecules and bulk materials. Supported by the U.S. DOE under Contract No. DOE-DE-FG05-08OR23336 and by the NSF under No. 0904572.

Design of optimized piezoelectric HDD-sliders

NASA Astrophysics Data System (ADS)

Nakasone, Paulo H.; Yoo, Jeonghoon; Silva, Emilio C. N.

2010-04-01

As storage data density in hard-disk drives (HDDs) increases for constant or miniaturizing sizes, precision positioning of HDD heads becomes a more relevant issue to ensure enormous amounts of data to be properly written and read. Since the traditional single-stage voice coil motor (VCM) cannot satisfy the positioning requirement of high-density tracks per inch (TPI) HDDs, dual-stage servo systems have been proposed to overcome this matter, by using VCMs to coarsely move the HDD head while piezoelectric actuators provides fine and fast positioning. Thus, the aim of this work is to apply topology optimization method (TOM) to design novel piezoelectric HDD heads, by finding optimal placement of base-plate and piezoelectric material to high precision positioning HDD heads. Topology optimization method is a structural optimization technique that combines the finite element method (FEM) with optimization algorithms. The laminated finite element employs the MITC (mixed interpolation of tensorial components) formulation to provide accurate and reliable results. The topology optimization uses a rational approximation of material properties to vary the material properties between 'void' and 'filled' portions. The design problem consists in generating optimal structures that provide maximal displacements, appropriate structural stiffness and resonance phenomena avoidance. The requirements are achieved by applying formulations to maximize displacements, minimize structural compliance and maximize resonance frequencies. This paper presents the implementation of the algorithms and show results to confirm the feasibility of this approach.

Range image registration based on hash map and moth-flame optimization

NASA Astrophysics Data System (ADS)

Zou, Li; Ge, Baozhen; Chen, Lei

2018-03-01

Over the past decade, evolutionary algorithms (EAs) have been introduced to solve range image registration problems because of their robustness and high precision. However, EA-based range image registration algorithms are time-consuming. To reduce the computational time, an EA-based range image registration algorithm using hash map and moth-flame optimization is proposed. In this registration algorithm, a hash map is used to avoid over-exploitation in registration process. Additionally, we present a search equation that is better at exploration and a restart mechanism to avoid being trapped in local minima. We compare the proposed registration algorithm with the registration algorithms using moth-flame optimization and several state-of-the-art EA-based registration algorithms. The experimental results show that the proposed algorithm has a lower computational cost than other algorithms and achieves similar registration precision.

Market-based control strategy for long-span structures considering the multi-time delay issue

NASA Astrophysics Data System (ADS)

Li, Hongnan; Song, Jianzhu; Li, Gang

2017-01-01

To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2 N precise algorithm was selected to solve the multi-time-delay issue for long-span structures based on the market-based control (MBC) method. The concept of interval mixed energy was introduced from computational structural mechanics and optimal control research areas, and it translates the design of the MBC multi-time-delay controller into a solution for the segment matrix. This approach transforms the serial algorithm in time to parallel computing in space, greatly improving the solving efficiency and numerical stability. The designed controller is able to consider the issue of time delay with a linear controlling force combination and is especially effective for large time-delay conditions. A numerical example of a long-span structure was selected to demonstrate the effectiveness of the presented controller, and the time delay was found to have a significant impact on the results.

Meshing complex macro-scale objects into self-assembling bricks

PubMed Central

Hacohen, Adar; Hanniel, Iddo; Nikulshin, Yasha; Wolfus, Shuki; Abu-Horowitz, Almogit; Bachelet, Ido

2015-01-01

Self-assembly provides an information-economical route to the fabrication of objects at virtually all scales. However, there is no known algorithm to program self-assembly in macro-scale, solid, complex 3D objects. Here such an algorithm is described, which is inspired by the molecular assembly of DNA, and based on bricks designed by tetrahedral meshing of arbitrary objects. Assembly rules are encoded by topographic cues imprinted on brick faces while attraction between bricks is provided by embedded magnets. The bricks can then be mixed in a container and agitated, leading to properly assembled objects at high yields and zero errors. The system and its assembly dynamics were characterized by video and audio analysis, enabling the precise time- and space-resolved characterization of its performance and accuracy. Improved designs inspired by our system could lead to successful implementation of self-assembly at the macro-scale, allowing rapid, on-demand fabrication of objects without the need for assembly lines. PMID:26226488

Quantum algorithms for quantum field theories.

PubMed

Jordan, Stephen P; Lee, Keith S M; Preskill, John

2012-06-01

Quantum field theory reconciles quantum mechanics and special relativity, and plays a central role in many areas of physics. We developed a quantum algorithm to compute relativistic scattering probabilities in a massive quantum field theory with quartic self-interactions (φ(4) theory) in spacetime of four and fewer dimensions. Its run time is polynomial in the number of particles, their energy, and the desired precision, and applies at both weak and strong coupling. In the strong-coupling and high-precision regimes, our quantum algorithm achieves exponential speedup over the fastest known classical algorithm.

An Elementary Algorithm to Evaluate Trigonometric Functions to High Precision

ERIC Educational Resources Information Center

Johansson, B. Tomas

2018-01-01

Evaluation of the cosine function is done via a simple Cordic-like algorithm, together with a package for handling arbitrary-precision arithmetic in the computer program Matlab. Approximations to the cosine function having hundreds of correct decimals are presented with a discussion around errors and implementation.

Model-based Bayesian signal extraction algorithm for peripheral nerves

NASA Astrophysics Data System (ADS)

Eggers, Thomas E.; Dweiri, Yazan M.; McCallum, Grant A.; Durand, Dominique M.

2017-10-01

Objective. Multi-channel cuff electrodes have recently been investigated for extracting fascicular-level motor commands from mixed neural recordings. Such signals could provide volitional, intuitive control over a robotic prosthesis for amputee patients. Recent work has demonstrated success in extracting these signals in acute and chronic preparations using spatial filtering techniques. These extracted signals, however, had low signal-to-noise ratios and thus limited their utility to binary classification. In this work a new algorithm is proposed which combines previous source localization approaches to create a model based method which operates in real time. Approach. To validate this algorithm, a saline benchtop setup was created to allow the precise placement of artificial sources within a cuff and interference sources outside the cuff. The artificial source was taken from five seconds of chronic neural activity to replicate realistic recordings. The proposed algorithm, hybrid Bayesian signal extraction (HBSE), is then compared to previous algorithms, beamforming and a Bayesian spatial filtering method, on this test data. An example chronic neural recording is also analyzed with all three algorithms. Main results. The proposed algorithm improved the signal to noise and signal to interference ratio of extracted test signals two to three fold, as well as increased the correlation coefficient between the original and recovered signals by 10-20%. These improvements translated to the chronic recording example and increased the calculated bit rate between the recovered signals and the recorded motor activity. Significance. HBSE significantly outperforms previous algorithms in extracting realistic neural signals, even in the presence of external noise sources. These results demonstrate the feasibility of extracting dynamic motor signals from a multi-fascicled intact nerve trunk, which in turn could extract motor command signals from an amputee for the end goal of controlling a prosthetic limb.

Recent Development of Multigrid Algorithms for Mixed and Noncomforming Methods for Second Order Elliptical Problems

NASA Technical Reports Server (NTRS)

Chen, Zhangxin; Ewing, Richard E.

1996-01-01

Multigrid algorithms for nonconforming and mixed finite element methods for second order elliptic problems on triangular and rectangular finite elements are considered. The construction of several coarse-to-fine intergrid transfer operators for nonconforming multigrid algorithms is discussed. The equivalence between the nonconforming and mixed finite element methods with and without projection of the coefficient of the differential problems into finite element spaces is described.

Different Trophic Tracers Give Different Answers for the Same Bugs - Comparing a Stable Isotope and Fatty Acid Based Analysis of Resource Utilization in a Marine Isopod

NASA Astrophysics Data System (ADS)

Galloway, A. W. E.; Eisenlord, M. E.; Brett, M. T.

2016-02-01

Stable isotope (SI) based mixing models are the most common approach used to infer resource pathways in consumers. However, SI based analyses are often underdetermined, and consumer SI fractionation is usually unknown. The use of fatty acid (FA) tracers in mixing models offers an alternative approach that can resolve the underdetermined constraint. A limitation to both methods is the considerable uncertainty about consumer `trophic modification' (TM) of dietary FA or SI, which occurs as consumers transform dietary resources into tissues. We tested the utility of SI and FA approaches for inferring the diets of the marine benthic isopod (Idotea wosnesenskii) fed various marine macroalgae in controlled feeding trials. Our analyses quantified how the accuracy and precision of Bayesian mixing models was influenced by choice of algorithm (SIAR vs MixSIR), fractionation (assumed or known), and whether the model was under or overdetermined (seven sources and two vs 26 tracers) for cases where isopods were fed an exclusive diet of one of the seven different macroalgae. Using the conventional approach (i.e., 2 SI with assumed TM) resulted in average model outputs, i.e., the contribution from the exclusive resource = 0.20 ± 0.23 (0.00-0.79), mean ± SD (95% credible interval), that only differed slightly from the prior assumption. Using the FA based approach with known TM greatly improved model performance, i.e., the contribution from the exclusive resource = 0.91 ± 0.10 (0.58-0.99). The choice of algorithm only made a difference when fractionation was known and the model was overdetermined (FA approach). In this case SIAR and MixSIR had outputs of 0.86 ± 0.11 (0.48-0.96) and 0.96 ± 0.05 (0.79-1.00), respectively. This analysis shows the choice of dietary tracers and the assumption of consumer trophic modification greatly influence the performance of mixing model dietary reconstructions, and ultimately our understanding of what resources actually support aquatic consumers.

[Primary branch size of Pinus koraiensis plantation: a prediction based on linear mixed effect model].

PubMed

Dong, Ling-Bo; Liu, Zhao-Gang; Li, Feng-Ri; Jiang, Li-Chun

2013-09-01

By using the branch analysis data of 955 standard branches from 60 sampled trees in 12 sampling plots of Pinus koraiensis plantation in Mengjiagang Forest Farm in Heilongjiang Province of Northeast China, and based on the linear mixed-effect model theory and methods, the models for predicting branch variables, including primary branch diameter, length, and angle, were developed. Considering tree effect, the MIXED module of SAS software was used to fit the prediction models. The results indicated that the fitting precision of the models could be improved by choosing appropriate random-effect parameters and variance-covariance structure. Then, the correlation structures including complex symmetry structure (CS), first-order autoregressive structure [AR(1)], and first-order autoregressive and moving average structure [ARMA(1,1)] were added to the optimal branch size mixed-effect model. The AR(1) improved the fitting precision of branch diameter and length mixed-effect model significantly, but all the three structures didn't improve the precision of branch angle mixed-effect model. In order to describe the heteroscedasticity during building mixed-effect model, the CF1 and CF2 functions were added to the branch mixed-effect model. CF1 function improved the fitting effect of branch angle mixed model significantly, whereas CF2 function improved the fitting effect of branch diameter and length mixed model significantly. Model validation confirmed that the mixed-effect model could improve the precision of prediction, as compare to the traditional regression model for the branch size prediction of Pinus koraiensis plantation.

Automated database-guided expert-supervised orientation for immunophenotypic diagnosis and classification of acute leukemia

PubMed Central

Lhermitte, L; Mejstrikova, E; van der Sluijs-Gelling, A J; Grigore, G E; Sedek, L; Bras, A E; Gaipa, G; Sobral da Costa, E; Novakova, M; Sonneveld, E; Buracchi, C; de Sá Bacelar, T; te Marvelde, J G; Trinquand, A; Asnafi, V; Szczepanski, T; Matarraz, S; Lopez, A; Vidriales, B; Bulsa, J; Hrusak, O; Kalina, T; Lecrevisse, Q; Martin Ayuso, M; Brüggemann, M; Verde, J; Fernandez, P; Burgos, L; Paiva, B; Pedreira, C E; van Dongen, J J M; Orfao, A; van der Velden, V H J

2018-01-01

Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide towards the relevant classification panel (T-cell acute lymphoblastic leukemia (T-ALL), B-cell precursor (BCP)-ALL and/or acute myeloid leukemia (AML)) and final diagnosis. Now we built a reference database with 656 typical AL samples (145 T-ALL, 377 BCP-ALL, 134 AML), processed and analyzed via standardized protocols. Using principal component analysis (PCA)-based plots and automated classification algorithms for direct comparison of single-cells from individual patients against the database, another 783 cases were subsequently evaluated. Depending on the database-guided results, patients were categorized as: (i) typical T, B or Myeloid without or; (ii) with a transitional component to another lineage; (iii) atypical; or (iv) mixed-lineage. Using this automated algorithm, in 781/783 cases (99.7%) the right panel was selected, and data comparable to the final WHO-diagnosis was already provided in >93% of cases (85% T-ALL, 97% BCP-ALL, 95% AML and 87% mixed-phenotype AL patients), even without data on the full-characterization panels. Our results show that database-guided analysis facilitates standardized interpretation of ALOT results and allows accurate selection of the relevant classification panels, hence providing a solid basis for designing future WHO AL classifications. PMID:29089646

Homotopy Algorithm for Fixed Order Mixed H2/H(infinity) Design

NASA Technical Reports Server (NTRS)

Whorton, Mark; Buschek, Harald; Calise, Anthony J.

1996-01-01

Recent developments in the field of robust multivariable control have merged the theories of H-infinity and H-2 control. This mixed H-2/H-infinity compensator formulation allows design for nominal performance by H-2 norm minimization while guaranteeing robust stability to unstructured uncertainties by constraining the H-infinity norm. A key difficulty associated with mixed H-2/H-infinity compensation is compensator synthesis. A homotopy algorithm is presented for synthesis of fixed order mixed H-2/H-infinity compensators. Numerical results are presented for a four disk flexible structure to evaluate the efficiency of the algorithm.

A Novel Zero Velocity Interval Detection Algorithm for Self-Contained Pedestrian Navigation System with Inertial Sensors

PubMed Central

Tian, Xiaochun; Chen, Jiabin; Han, Yongqiang; Shang, Jianyu; Li, Nan

2016-01-01

Zero velocity update (ZUPT) plays an important role in pedestrian navigation algorithms with the premise that the zero velocity interval (ZVI) should be detected accurately and effectively. A novel adaptive ZVI detection algorithm based on a smoothed pseudo Wigner–Ville distribution to remove multiple frequencies intelligently (SPWVD-RMFI) is proposed in this paper. The novel algorithm adopts the SPWVD-RMFI method to extract the pedestrian gait frequency and to calculate the optimal ZVI detection threshold in real time by establishing the function relationships between the thresholds and the gait frequency; then, the adaptive adjustment of thresholds with gait frequency is realized and improves the ZVI detection precision. To put it into practice, a ZVI detection experiment is carried out; the result shows that compared with the traditional fixed threshold ZVI detection method, the adaptive ZVI detection algorithm can effectively reduce the false and missed detection rate of ZVI; this indicates that the novel algorithm has high detection precision and good robustness. Furthermore, pedestrian trajectory positioning experiments at different walking speeds are carried out to evaluate the influence of the novel algorithm on positioning precision. The results show that the ZVI detected by the adaptive ZVI detection algorithm for pedestrian trajectory calculation can achieve better performance. PMID:27669266

Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators

NASA Technical Reports Server (NTRS)

Zhou, Zhiqiang

2012-01-01

A paper describes attitude-control algorithms using the combination of magnetic actuators with reaction wheel assemblies (RWAs) or other types of actuators such as thrusters. The combination of magnetic actuators with one or two RWAs aligned with different body axis expands the two-dimensional control torque to three-dimensional. The algorithms can guarantee the spacecraft attitude and rates to track the commanded attitude precisely. A design example is presented for nadir-pointing, pitch, and yaw maneuvers. The results show that precise attitude tracking can be reached and the attitude- control accuracy is comparable with RWA-based attitude control. When there are only one or two workable RWAs due to RWA failures, the attitude-control system can switch to the control algorithms for the combined magnetic actuators with the RWAs without going to the safe mode, and the control accuracy can be maintained. The attitude-control algorithms of the combined actuators are derived, which can guarantee the spacecraft attitude and rates to track the commanded values precisely. Results show that precise attitude tracking can be reached, and the attitude-control accuracy is comparable with 3-axis wheel control.

Solving lattice QCD systems of equations using mixed precision solvers on GPUs

NASA Astrophysics Data System (ADS)

Clark, M. A.; Babich, R.; Barros, K.; Brower, R. C.; Rebbi, C.

2010-09-01

Modern graphics hardware is designed for highly parallel numerical tasks and promises significant cost and performance benefits for many scientific applications. One such application is lattice quantum chromodynamics (lattice QCD), where the main computational challenge is to efficiently solve the discretized Dirac equation in the presence of an SU(3) gauge field. Using NVIDIA's CUDA platform we have implemented a Wilson-Dirac sparse matrix-vector product that performs at up to 40, 135 and 212 Gflops for double, single and half precision respectively on NVIDIA's GeForce GTX 280 GPU. We have developed a new mixed precision approach for Krylov solvers using reliable updates which allows for full double precision accuracy while using only single or half precision arithmetic for the bulk of the computation. The resulting BiCGstab and CG solvers run in excess of 100 Gflops and, in terms of iterations until convergence, perform better than the usual defect-correction approach for mixed precision.

Using Radar, Lidar, and Radiometer measurements to Classify Cloud Type and Study Middle-Level Cloud Properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhien

2010-06-29

The project is mainly focused on the characterization of cloud macrophysical and microphysical properties, especially for mixed-phased clouds and middle level ice clouds by combining radar, lidar, and radiometer measurements available from the ACRF sites. First, an advanced mixed-phase cloud retrieval algorithm will be developed to cover all mixed-phase clouds observed at the ACRF NSA site. The algorithm will be applied to the ACRF NSA observations to generate a long-term arctic mixed-phase cloud product for model validations and arctic mixed-phase cloud processes studies. To improve the representation of arctic mixed-phase clouds in GCMs, an advanced understanding of mixed-phase cloud processesmore » is needed. By combining retrieved mixed-phase cloud microphysical properties with in situ data and large-scale meteorological data, the project aim to better understand the generations of ice crystals in supercooled water clouds, the maintenance mechanisms of the arctic mixed-phase clouds, and their connections with large-scale dynamics. The project will try to develop a new retrieval algorithm to study more complex mixed-phase clouds observed at the ACRF SGP site. Compared with optically thin ice clouds, optically thick middle level ice clouds are less studied because of limited available tools. The project will develop a new two wavelength radar technique for optically thick ice cloud study at SGP site by combining the MMCR with the W-band radar measurements. With this new algorithm, the SGP site will have a better capability to study all ice clouds. Another area of the proposal is to generate long-term cloud type classification product for the multiple ACRF sites. The cloud type classification product will not only facilitates the generation of the integrated cloud product by applying different retrieval algorithms to different types of clouds operationally, but will also support other research to better understand cloud properties and to validate model simulations. The ultimate goal is to improve our cloud classification algorithm into a VAP.« less

Identification of Patients with Family History of Pancreatic Cancer--Investigation of an NLP System Portability.

PubMed

Mehrabi, Saeed; Krishnan, Anand; Roch, Alexandra M; Schmidt, Heidi; Li, DingCheng; Kesterson, Joe; Beesley, Chris; Dexter, Paul; Schmidt, Max; Palakal, Mathew; Liu, Hongfang

2015-01-01

In this study we have developed a rule-based natural language processing (NLP) system to identify patients with family history of pancreatic cancer. The algorithm was developed in a Unstructured Information Management Architecture (UIMA) framework and consisted of section segmentation, relation discovery, and negation detection. The system was evaluated on data from two institutions. The family history identification precision was consistent across the institutions shifting from 88.9% on Indiana University (IU) dataset to 87.8% on Mayo Clinic dataset. Customizing the algorithm on the the Mayo Clinic data, increased its precision to 88.1%. The family member relation discovery achieved precision, recall, and F-measure of 75.3%, 91.6% and 82.6% respectively. Negation detection resulted in precision of 99.1%. The results show that rule-based NLP approaches for specific information extraction tasks are portable across institutions; however customization of the algorithm on the new dataset improves its performance.

Algorithm-based arterial blood sampling recognition increasing safety in point-of-care diagnostics.

PubMed

Peter, Jörg; Klingert, Wilfried; Klingert, Kathrin; Thiel, Karolin; Wulff, Daniel; Königsrainer, Alfred; Rosenstiel, Wolfgang; Schenk, Martin

2017-08-04

To detect blood withdrawal for patients with arterial blood pressure monitoring to increase patient safety and provide better sample dating. Blood pressure information obtained from a patient monitor was fed as a real-time data stream to an experimental medical framework. This framework was connected to an analytical application which observes changes in systolic, diastolic and mean pressure to determine anomalies in the continuous data stream. Detection was based on an increased mean blood pressure caused by the closing of the withdrawal three-way tap and an absence of systolic and diastolic measurements during this manipulation. For evaluation of the proposed algorithm, measured data from animal studies in healthy pigs were used. Using this novel approach for processing real-time measurement data of arterial pressure monitoring, the exact time of blood withdrawal could be successfully detected retrospectively and in real-time. The algorithm was able to detect 422 of 434 (97%) blood withdrawals for blood gas analysis in the retrospective analysis of 7 study trials. Additionally, 64 sampling events for other procedures like laboratory and activated clotting time analyses were detected. The proposed algorithm achieved a sensitivity of 0.97, a precision of 0.96 and an F1 score of 0.97. Arterial blood pressure monitoring data can be used to perform an accurate identification of individual blood samplings in order to reduce sample mix-ups and thereby increase patient safety.

CONEDEP: COnvolutional Neural network based Earthquake DEtection and Phase Picking

NASA Astrophysics Data System (ADS)

Zhou, Y.; Huang, Y.; Yue, H.; Zhou, S.; An, S.; Yun, N.

2017-12-01

We developed an automatic local earthquake detection and phase picking algorithm based on Fully Convolutional Neural network (FCN). The FCN algorithm detects and segments certain features (phases) in 3 component seismograms to realize efficient picking. We use STA/LTA algorithm and template matching algorithm to construct the training set from seismograms recorded 1 month before and after the Wenchuan earthquake. Precise P and S phases are identified and labeled to construct the training set. Noise data are produced by combining back-ground noise and artificial synthetic noise to form the equivalent scale of noise set as the signal set. Training is performed on GPUs to achieve efficient convergence. Our algorithm has significantly improved performance in terms of the detection rate and precision in comparison with STA/LTA and template matching algorithms.

Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

NASA Technical Reports Server (NTRS)

Yu, Yifan; Saatchi, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri

2010-01-01

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P < 0.001; RMSE = 1.1 m) and mixed forests (R2 = 0.93, P < 0.001, RMSE = 0.8 m) produced the best results. Estimates over deciduous forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

Developing a system for blind acoustic source localization and separation

NASA Astrophysics Data System (ADS)

Kulkarni, Raghavendra

This dissertation presents innovate methodologies for locating, extracting, and separating multiple incoherent sound sources in three-dimensional (3D) space; and applications of the time reversal (TR) algorithm to pinpoint the hyper active neural activities inside the brain auditory structure that are correlated to the tinnitus pathology. Specifically, an acoustic modeling based method is developed for locating arbitrary and incoherent sound sources in 3D space in real time by using a minimal number of microphones, and the Point Source Separation (PSS) method is developed for extracting target signals from directly measured mixed signals. Combining these two approaches leads to a novel technology known as Blind Sources Localization and Separation (BSLS) that enables one to locate multiple incoherent sound signals in 3D space and separate original individual sources simultaneously, based on the directly measured mixed signals. These technologies have been validated through numerical simulations and experiments conducted in various non-ideal environments where there are non-negligible, unspecified sound reflections and reverberation as well as interferences from random background noise. Another innovation presented in this dissertation is concerned with applications of the TR algorithm to pinpoint the exact locations of hyper-active neurons in the brain auditory structure that are directly correlated to the tinnitus perception. Benchmark tests conducted on normal rats have confirmed the localization results provided by the TR algorithm. Results demonstrate that the spatial resolution of this source localization can be as high as the micrometer level. This high precision localization may lead to a paradigm shift in tinnitus diagnosis, which may in turn produce a more cost-effective treatment for tinnitus than any of the existing ones.

Design optimization of single mixed refrigerant LNG process using a hybrid modified coordinate descent algorithm

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong

2018-01-01

Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.

Extended Mixed-Efects Item Response Models with the MH-RM Algorithm

ERIC Educational Resources Information Center

Chalmers, R. Philip

2015-01-01

A mixed-effects item response theory (IRT) model is presented as a logical extension of the generalized linear mixed-effects modeling approach to formulating explanatory IRT models. Fixed and random coefficients in the extended model are estimated using a Metropolis-Hastings Robbins-Monro (MH-RM) stochastic imputation algorithm to accommodate for…

Mathematical model and metaheuristics for simultaneous balancing and sequencing of a robotic mixed-model assembly line

NASA Astrophysics Data System (ADS)

Li, Zixiang; Janardhanan, Mukund Nilakantan; Tang, Qiuhua; Nielsen, Peter

2018-05-01

This article presents the first method to simultaneously balance and sequence robotic mixed-model assembly lines (RMALB/S), which involves three sub-problems: task assignment, model sequencing and robot allocation. A new mixed-integer programming model is developed to minimize makespan and, using CPLEX solver, small-size problems are solved for optimality. Two metaheuristics, the restarted simulated annealing algorithm and co-evolutionary algorithm, are developed and improved to address this NP-hard problem. The restarted simulated annealing method replaces the current temperature with a new temperature to restart the search process. The co-evolutionary method uses a restart mechanism to generate a new population by modifying several vectors simultaneously. The proposed algorithms are tested on a set of benchmark problems and compared with five other high-performing metaheuristics. The proposed algorithms outperform their original editions and the benchmarked methods. The proposed algorithms are able to solve the balancing and sequencing problem of a robotic mixed-model assembly line effectively and efficiently.

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

PubMed

Shen, Lili; Guo, Jiming; Wang, Lei

2018-06-06

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

The research of radar target tracking observed information linear filter method

NASA Astrophysics Data System (ADS)

Chen, Zheng; Zhao, Xuanzhi; Zhang, Wen

2018-05-01

Aiming at the problems of low precision or even precision divergent is caused by nonlinear observation equation in radar target tracking, a new filtering algorithm is proposed in this paper. In this algorithm, local linearization is carried out on the observed data of the distance and angle respectively. Then the kalman filter is performed on the linearized data. After getting filtered data, a mapping operation will provide the posteriori estimation of target state. A large number of simulation results show that this algorithm can solve above problems effectively, and performance is better than the traditional filtering algorithm for nonlinear dynamic systems.

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging.

PubMed

Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

2017-11-07

This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

Research on sparse feature matching of improved RANSAC algorithm

NASA Astrophysics Data System (ADS)

Kong, Xiangsi; Zhao, Xian

2018-04-01

In this paper, a sparse feature matching method based on modified RANSAC algorithm is proposed to improve the precision and speed. Firstly, the feature points of the images are extracted using the SIFT algorithm. Then, the image pair is matched roughly by generating SIFT feature descriptor. At last, the precision of image matching is optimized by the modified RANSAC algorithm,. The RANSAC algorithm is improved from three aspects: instead of the homography matrix, this paper uses the fundamental matrix generated by the 8 point algorithm as the model; the sample is selected by a random block selecting method, which ensures the uniform distribution and the accuracy; adds sequential probability ratio test(SPRT) on the basis of standard RANSAC, which cut down the overall running time of the algorithm. The experimental results show that this method can not only get higher matching accuracy, but also greatly reduce the computation and improve the matching speed.

SPH investigation of the thermal effects on the fluid mixing in a microchannel with rotating stirrers

NASA Astrophysics Data System (ADS)

Shamsoddini, Rahim

2018-04-01

An incompressible smoothed particle hydrodynamics algorithm is proposed to model and investigate the thermal effect on the mixing rate of an active micromixer in which the rotating stirrers enhance the mixing rate. In liquids, mass diffusion increases with increasing temperature, while viscosity decreases; so, the local Schmidt number decreases considerably with increasing temperature. The present study investigates the effect of wall temperature on mixing rate with an improved SPH method. The robust SPH method used in the present work is equipped with a shifting algorithm and renormalization tensors. By introducing this new algorithm, the several mass, momentum, energy, and concentration equations are solved. The results, discussed for different temperature ratios, show that mixing rate increases significantly with increased temperature ratio.

Volumetric display containing multiple two-dimensional color motion pictures

NASA Astrophysics Data System (ADS)

Hirayama, R.; Shiraki, A.; Nakayama, H.; Kakue, T.; Shimobaba, T.; Ito, T.

2014-06-01

We have developed an algorithm which can record multiple two-dimensional (2-D) gradated projection patterns in a single three-dimensional (3-D) object. Each recorded pattern has the individual projected direction and can only be seen from the direction. The proposed algorithm has two important features: the number of recorded patterns is theoretically infinite and no meaningful pattern can be seen outside of the projected directions. In this paper, we expanded the algorithm to record multiple 2-D projection patterns in color. There are two popular ways of color mixing: additive one and subtractive one. Additive color mixing used to mix light is based on RGB colors and subtractive color mixing used to mix inks is based on CMY colors. We made two coloring methods based on the additive mixing and subtractive mixing. We performed numerical simulations of the coloring methods, and confirmed their effectiveness. We also fabricated two types of volumetric display and applied the proposed algorithm to them. One is a cubic displays constructed by light-emitting diodes (LEDs) in 8×8×8 array. Lighting patterns of LEDs are controlled by a microcomputer board. The other one is made of 7×7 array of threads. Each thread is illuminated by a projector connected with PC. As a result of the implementation, we succeeded in recording multiple 2-D color motion pictures in the volumetric displays. Our algorithm can be applied to digital signage, media art and so forth.

Mixing times in quantum walks on two-dimensional grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marquezino, F. L.; Portugal, R.; Abal, G.

2010-10-15

Mixing properties of discrete-time quantum walks on two-dimensional grids with toruslike boundary conditions are analyzed, focusing on their connection to the complexity of the corresponding abstract search algorithm. In particular, an exact expression for the stationary distribution of the coherent walk over odd-sided lattices is obtained after solving the eigenproblem for the evolution operator for this particular graph. The limiting distribution and mixing time of a quantum walk with a coin operator modified as in the abstract search algorithm are obtained numerically. On the basis of these results, the relation between the mixing time of the modified walk and themore » running time of the corresponding abstract search algorithm is discussed.« less

Mixing times in quantum walks on two-dimensional grids

NASA Astrophysics Data System (ADS)

Marquezino, F. L.; Portugal, R.; Abal, G.

2010-10-01

Mixing properties of discrete-time quantum walks on two-dimensional grids with toruslike boundary conditions are analyzed, focusing on their connection to the complexity of the corresponding abstract search algorithm. In particular, an exact expression for the stationary distribution of the coherent walk over odd-sided lattices is obtained after solving the eigenproblem for the evolution operator for this particular graph. The limiting distribution and mixing time of a quantum walk with a coin operator modified as in the abstract search algorithm are obtained numerically. On the basis of these results, the relation between the mixing time of the modified walk and the running time of the corresponding abstract search algorithm is discussed.

Precision experiments on mirror transitions at Notre Dame

NASA Astrophysics Data System (ADS)

Brodeur, Maxime; TwinSol Collaboration

2016-09-01

Thanks to extensive experimental efforts that led to a precise determination of important experimental quantities of superallowed pure Fermi transitions, we now have a very precise value for Vud that leads to a stringent test of the CKM matrix unitarity. Despite this achievement, measurements in other systems remain relevant as conflicting results could uncover unknown systematic effects or even new physics. One such system is the superallowed mixed transition, which can help refine theoretical corrections used for pure Fermi transitions and improve the accuracy of Vud. However, as a corrected Ft-value determination from these systems requires the more challenging determination of the Fermi Gamow-Teller mixing ratio, only five transitions, spreading from 19Ne to 37Ar, are currently fully characterized. To rectify the situation, an experimental program on precision experiment of mirror transitions that includes precision half-life measurements, and in the future, the determination of the Fermi Gamow-Teller mixing ratio, has started at the University of Notre Dame. This work is supported in part by the National Science Foundation.

Identification of Patients with Family History of Pancreatic Cancer - Investigation of an NLP System Portability

PubMed Central

Mehrabi, Saeed; Krishnan, Anand; Roch, Alexandra M; Schmidt, Heidi; Li, DingCheng; Kesterson, Joe; Beesley, Chris; Dexter, Paul; Schmidt, Max; Palakal, Mathew; Liu, Hongfang

2018-01-01

In this study we have developed a rule-based natural language processing (NLP) system to identify patients with family history of pancreatic cancer. The algorithm was developed in a Unstructured Information Management Architecture (UIMA) framework and consisted of section segmentation, relation discovery, and negation detection. The system was evaluated on data from two institutions. The family history identification precision was consistent across the institutions shifting from 88.9% on Indiana University (IU) dataset to 87.8% on Mayo Clinic dataset. Customizing the algorithm on the the Mayo Clinic data, increased its precision to 88.1%. The family member relation discovery achieved precision, recall, and F-measure of 75.3%, 91.6% and 82.6% respectively. Negation detection resulted in precision of 99.1%. The results show that rule-based NLP approaches for specific information extraction tasks are portable across institutions; however customization of the algorithm on the new dataset improves its performance. PMID:26262122

Quantifying auditory temporal stability in a large database of recorded music.

PubMed

Ellis, Robert J; Duan, Zhiyan; Wang, Ye

2014-01-01

"Moving to the beat" is both one of the most basic and one of the most profound means by which humans (and a few other species) interact with music. Computer algorithms that detect the precise temporal location of beats (i.e., pulses of musical "energy") in recorded music have important practical applications, such as the creation of playlists with a particular tempo for rehabilitation (e.g., rhythmic gait training), exercise (e.g., jogging), or entertainment (e.g., continuous dance mixes). Although several such algorithms return simple point estimates of an audio file's temporal structure (e.g., "average tempo", "time signature"), none has sought to quantify the temporal stability of a series of detected beats. Such a method--a "Balanced Evaluation of Auditory Temporal Stability" (BEATS)--is proposed here, and is illustrated using the Million Song Dataset (a collection of audio features and music metadata for nearly one million audio files). A publically accessible web interface is also presented, which combines the thresholdable statistics of BEATS with queryable metadata terms, fostering potential avenues of research and facilitating the creation of highly personalized music playlists for clinical or recreational applications.

Using an Extended Kalman Filter Learning Algorithm for Feed-Forward Neural Networks to Describe Tracer Correlations

NASA Technical Reports Server (NTRS)

Lary, David J.; Mussa, Yussuf

2004-01-01

In this study a new extended Kalman filter (EKF) learning algorithm for feed-forward neural networks (FFN) is used. With the EKF approach, the training of the FFN can be seen as state estimation for a non-linear stationary process. The EKF method gives excellent convergence performances provided that there is enough computer core memory and that the machine precision is high. Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH4 volume mixing ratio (v.m.r.). The neural network was able to reproduce the CH4-N2O correlation with a correlation coefficient between simulated and training values of 0.9997. The neural network Fortran code used is available for download.

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

PubMed Central

He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

2017-01-01

This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data. PMID:29112151

Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms.

PubMed

De Sa, Christopher; Zhang, Ce; Olukotun, Kunle; Ré, Christopher

2015-12-01

Stochastic gradient descent (SGD) is a ubiquitous algorithm for a variety of machine learning problems. Researchers and industry have developed several techniques to optimize SGD's runtime performance, including asynchronous execution and reduced precision. Our main result is a martingale-based analysis that enables us to capture the rich noise models that may arise from such techniques. Specifically, we use our new analysis in three ways: (1) we derive convergence rates for the convex case (Hogwild!) with relaxed assumptions on the sparsity of the problem; (2) we analyze asynchronous SGD algorithms for non-convex matrix problems including matrix completion; and (3) we design and analyze an asynchronous SGD algorithm, called Buckwild!, that uses lower-precision arithmetic. We show experimentally that our algorithms run efficiently for a variety of problems on modern hardware.

Study of image matching algorithm and sub-pixel fitting algorithm in target tracking

NASA Astrophysics Data System (ADS)

Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu

2015-03-01

Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image was processed by mean filter and median filter, then image matching was processed. The result show that when the noise is little, mean filter and median filter can achieve a good result. But when the noise density of salt and pepper noise is bigger than 0.4, or the variance of Gaussian noise is bigger than 0.0015, the result of image matching will be wrong.

Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2015-01-01

The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189

Trajectory NG: portable, compressed, general molecular dynamics trajectories.

PubMed

Spångberg, Daniel; Larsson, Daniel S D; van der Spoel, David

2011-10-01

We present general algorithms for the compression of molecular dynamics trajectories. The standard ways to store MD trajectories as text or as raw binary floating point numbers result in very large files when efficient simulation programs are used on supercomputers. Our algorithms are based on the observation that differences in atomic coordinates/velocities, in either time or space, are generally smaller than the absolute values of the coordinates/velocities. Also, it is often possible to store values at a lower precision. We apply several compression schemes to compress the resulting differences further. The most efficient algorithms developed here use a block sorting algorithm in combination with Huffman coding. Depending on the frequency of storage of frames in the trajectory, either space, time, or combinations of space and time differences are usually the most efficient. We compare the efficiency of our algorithms with each other and with other algorithms present in the literature for various systems: liquid argon, water, a virus capsid solvated in 15 mM aqueous NaCl, and solid magnesium oxide. We perform tests to determine how much precision is necessary to obtain accurate structural and dynamic properties, as well as benchmark a parallelized implementation of the algorithms. We obtain compression ratios (compared to single precision floating point) of 1:3.3-1:35 depending on the frequency of storage of frames and the system studied.

An Image-Based Algorithm for Precise and Accurate High Throughput Assessment of Drug Activity against the Human Parasite Trypanosoma cruzi

PubMed Central

Moraes, Carolina Borsoi; Yang, Gyongseon; Kang, Myungjoo; Freitas-Junior, Lucio H.; Hansen, Michael A. E.

2014-01-01

We present a customized high content (image-based) and high throughput screening algorithm for the quantification of Trypanosoma cruzi infection in host cells. Based solely on DNA staining and single-channel images, the algorithm precisely segments and identifies the nuclei and cytoplasm of mammalian host cells as well as the intracellular parasites infecting the cells. The algorithm outputs statistical parameters including the total number of cells, number of infected cells and the total number of parasites per image, the average number of parasites per infected cell, and the infection ratio (defined as the number of infected cells divided by the total number of cells). Accurate and precise estimation of these parameters allow for both quantification of compound activity against parasites, as well as the compound cytotoxicity, thus eliminating the need for an additional toxicity-assay, hereby reducing screening costs significantly. We validate the performance of the algorithm using two known drugs against T.cruzi: Benznidazole and Nifurtimox. Also, we have checked the performance of the cell detection with manual inspection of the images. Finally, from the titration of the two compounds, we confirm that the algorithm provides the expected half maximal effective concentration (EC50) of the anti-T. cruzi activity. PMID:24503652

Developing a New Wireless Sensor Network Platform and Its Application in Precision Agriculture

PubMed Central

Aquino-Santos, Raúl; González-Potes, Apolinar; Edwards-Block, Arthur; Virgen-Ortiz, Raúl Alejandro

2011-01-01

Wireless sensor networks are gaining greater attention from the research community and industrial professionals because these small pieces of “smart dust” offer great advantages due to their small size, low power consumption, easy integration and support for “green” applications. Green applications are considered a hot topic in intelligent environments, ubiquitous and pervasive computing. This work evaluates a new wireless sensor network platform and its application in precision agriculture, including its embedded operating system and its routing algorithm. To validate the technological platform and the embedded operating system, two different routing strategies were compared: hierarchical and flat. Both of these routing algorithms were tested in a small-scale network applied to a watermelon field. However, we strongly believe that this technological platform can be also applied to precision agriculture because it incorporates a modified version of LORA-CBF, a wireless location-based routing algorithm that uses cluster-based flooding. Cluster-based flooding addresses the scalability concerns of wireless sensor networks, while the modified LORA-CBF routing algorithm includes a metric to monitor residual battery energy. Furthermore, results show that the modified version of LORA-CBF functions well with both the flat and hierarchical algorithms, although it functions better with the flat algorithm in a small-scale agricultural network. PMID:22346622

Developing a new wireless sensor network platform and its application in precision agriculture.

PubMed

Aquino-Santos, Raúl; González-Potes, Apolinar; Edwards-Block, Arthur; Virgen-Ortiz, Raúl Alejandro

2011-01-01

Wireless sensor networks are gaining greater attention from the research community and industrial professionals because these small pieces of "smart dust" offer great advantages due to their small size, low power consumption, easy integration and support for "green" applications. Green applications are considered a hot topic in intelligent environments, ubiquitous and pervasive computing. This work evaluates a new wireless sensor network platform and its application in precision agriculture, including its embedded operating system and its routing algorithm. To validate the technological platform and the embedded operating system, two different routing strategies were compared: hierarchical and flat. Both of these routing algorithms were tested in a small-scale network applied to a watermelon field. However, we strongly believe that this technological platform can be also applied to precision agriculture because it incorporates a modified version of LORA-CBF, a wireless location-based routing algorithm that uses cluster-based flooding. Cluster-based flooding addresses the scalability concerns of wireless sensor networks, while the modified LORA-CBF routing algorithm includes a metric to monitor residual battery energy. Furthermore, results show that the modified version of LORA-CBF functions well with both the flat and hierarchical algorithms, although it functions better with the flat algorithm in a small-scale agricultural network.

Asteroseismic Constraints on the Models of Hot B Subdwarfs: Convective Helium-Burning Cores

NASA Astrophysics Data System (ADS)

Schindler, Jan-Torge; Green, Elizabeth M.; Arnett, W. David

2017-10-01

Asteroseismology of non-radial pulsations in Hot B Subdwarfs (sdB stars) offers a unique view into the interior of core-helium-burning stars. Ground-based and space-borne high precision light curves allow for the analysis of pressure and gravity mode pulsations to probe the structure of sdB stars deep into the convective core. As such asteroseismological analysis provides an excellent opportunity to test our understanding of stellar evolution. In light of the newest constraints from asteroseismology of sdB and red clump stars, standard approaches of convective mixing in 1D stellar evolution models are called into question. The problem lies in the current treatment of overshooting and the entrainment at the convective boundary. Unfortunately no consistent algorithm of convective mixing exists to solve the problem, introducing uncertainties to the estimates of stellar ages. Three dimensional simulations of stellar convection show the natural development of an overshooting region and a boundary layer. In search for a consistent prescription of convection in one dimensional stellar evolution models, guidance from three dimensional simulations and asteroseismological results is indispensable.

Algorithmic and heuristic processing of information by the nervous system.

PubMed

Restian, A

1980-01-01

Starting from the fact that the nervous system must discover the information it needs, the author describes the way it decodes the received message. The logical circuits of the nervous system, submitting the received signals to a process by means of which information brought is discovered step by step, participates in decoding the message. The received signals, as information, can be algorithmically or heuristically processed. Algorithmic processing is done according to precise rules, which must be fulfilled step by step. By algorithmic processing, one develops somatic and vegetative reflexes as blood pressure, heart frequency or water metabolism control. When it does not dispose of precise rules of information processing or when algorithmic processing needs a very long time, the nervous system must use heuristic processing. This is the feature that differentiates the human brain from the electronic computer that can work only according to some extremely precise rules. The human brain can work according to less precise rules because it can resort to trial and error operations, and because it works according to a form of logic. Working with superior order signals which represent the class of all inferior type signals from which they begin, the human brain need not perform all the operations that it would have to perform by superior type of signals. Therefore the brain tries to submit the received signals to intensive as possible superization. All informational processing, and especially heuristical processing, is accompanied by a certain affective color and the brain cannot operate without it. Emotions, passions and sentiments usually complete the lack of precision of the heuristical programmes. Finally, the author shows that informational and especially heuristical processes study can contribute to a better understanding of the transition from neurological to psychological activity.

Variational study on the vibrational level structure and vibrational level mixing of highly vibrationally excited S₀ D₂CO.

PubMed

Rashev, Svetoslav; Moule, David C; Rashev, Vladimir

2012-11-01

We perform converged high precision variational calculations to determine the frequencies of a large number of vibrational levels in S(0) D(2)CO, extending from low to very high excess vibrational energies. For the calculations we use our specific vibrational method (recently employed for studies on H(2)CO), consisting of a combination of a search/selection algorithm and a Lanczos iteration procedure. Using the same method we perform large scale converged calculations on the vibrational level spectral structure and fragmentation at selected highly excited overtone states, up to excess vibrational energies of ∼17,000 cm(-1), in order to study the characteristics of intramolecular vibrational redistribution (IVR), vibrational level density and mode selectivity. Copyright © 2012 Elsevier B.V. All rights reserved.

A Robust Wireless Sensor Network Localization Algorithm in Mixed LOS/NLOS Scenario.

PubMed

Li, Bing; Cui, Wei; Wang, Bin

2015-09-16

Localization algorithms based on received signal strength indication (RSSI) are widely used in the field of target localization due to its advantages of convenient application and independent from hardware devices. Unfortunately, the RSSI values are susceptible to fluctuate under the influence of non-line-of-sight (NLOS) in indoor space. Existing algorithms often produce unreliable estimated distances, leading to low accuracy and low effectiveness in indoor target localization. Moreover, these approaches require extra prior knowledge about the propagation model. As such, we focus on the problem of localization in mixed LOS/NLOS scenario and propose a novel localization algorithm: Gaussian mixed model based non-metric Multidimensional (GMDS). In GMDS, the RSSI is estimated using a Gaussian mixed model (GMM). The dissimilarity matrix is built to generate relative coordinates of nodes by a multi-dimensional scaling (MDS) approach. Finally, based on the anchor nodes' actual coordinates and target's relative coordinates, the target's actual coordinates can be computed via coordinate transformation. Our algorithm could perform localization estimation well without being provided with prior knowledge. The experimental verification shows that GMDS effectively reduces NLOS error and is of higher accuracy in indoor mixed LOS/NLOS localization and still remains effective when we extend single NLOS to multiple NLOS.

A new optimized GA-RBF neural network algorithm.

PubMed

Jia, Weikuan; Zhao, Dean; Shen, Tian; Su, Chunyang; Hu, Chanli; Zhao, Yuyan

2014-01-01

When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and recognition precision. Aiming at this problem, we propose a new optimized RBF neural network algorithm based on genetic algorithm (GA-RBF algorithm), which uses genetic algorithm to optimize the weights and structure of RBF neural network; it chooses new ways of hybrid encoding and optimizing simultaneously. Using the binary encoding encodes the number of the hidden layer's neurons and using real encoding encodes the connection weights. Hidden layer neurons number and connection weights are optimized simultaneously in the new algorithm. However, the connection weights optimization is not complete; we need to use least mean square (LMS) algorithm for further leaning, and finally get a new algorithm model. Using two UCI standard data sets to test the new algorithm, the results show that the new algorithm improves the operating efficiency in dealing with complex problems and also improves the recognition precision, which proves that the new algorithm is valid.

influx_s: increasing numerical stability and precision for metabolic flux analysis in isotope labelling experiments.

PubMed

Sokol, Serguei; Millard, Pierre; Portais, Jean-Charles

2012-03-01

The problem of stationary metabolic flux analysis based on isotope labelling experiments first appeared in the early 1950s and was basically solved in early 2000s. Several algorithms and software packages are available for this problem. However, the generic stochastic algorithms (simulated annealing or evolution algorithms) currently used in these software require a lot of time to achieve acceptable precision. For deterministic algorithms, a common drawback is the lack of convergence stability for ill-conditioned systems or when started from a random point. In this article, we present a new deterministic algorithm with significantly increased numerical stability and accuracy of flux estimation compared with commonly used algorithms. It requires relatively short CPU time (from several seconds to several minutes with a standard PC architecture) to estimate fluxes in the central carbon metabolism network of Escherichia coli. The software package influx_s implementing this algorithm is distributed under an OpenSource licence at http://metasys.insa-toulouse.fr/software/influx/. Supplementary data are available at Bioinformatics online.

A robust statistical estimation (RoSE) algorithm jointly recovers the 3D location and intensity of single molecules accurately and precisely

NASA Astrophysics Data System (ADS)

Mazidi, Hesam; Nehorai, Arye; Lew, Matthew D.

2018-02-01

In single-molecule (SM) super-resolution microscopy, the complexity of a biological structure, high molecular density, and a low signal-to-background ratio (SBR) may lead to imaging artifacts without a robust localization algorithm. Moreover, engineered point spread functions (PSFs) for 3D imaging pose difficulties due to their intricate features. We develop a Robust Statistical Estimation algorithm, called RoSE, that enables joint estimation of the 3D location and photon counts of SMs accurately and precisely using various PSFs under conditions of high molecular density and low SBR.

High-precision positioning system of four-quadrant detector based on the database query

NASA Astrophysics Data System (ADS)

Zhang, Xin; Deng, Xiao-guo; Su, Xiu-qin; Zheng, Xiao-qiang

2015-02-01

The fine pointing mechanism of the Acquisition, Pointing and Tracking (APT) system in free space laser communication usually use four-quadrant detector (QD) to point and track the laser beam accurately. The positioning precision of QD is one of the key factors of the pointing accuracy to APT system. A positioning system is designed based on FPGA and DSP in this paper, which can realize the sampling of AD, the positioning algorithm and the control of the fast swing mirror. We analyze the positioning error of facular center calculated by universal algorithm when the facular energy obeys Gauss distribution from the working principle of QD. A database is built by calculation and simulation with MatLab software, in which the facular center calculated by universal algorithm is corresponded with the facular center of Gaussian beam, and the database is stored in two pieces of E2PROM as the external memory of DSP. The facular center of Gaussian beam is inquiry in the database on the basis of the facular center calculated by universal algorithm in DSP. The experiment results show that the positioning accuracy of the high-precision positioning system is much better than the positioning accuracy calculated by universal algorithm.

High Precision Edge Detection Algorithm for Mechanical Parts

NASA Astrophysics Data System (ADS)

Duan, Zhenyun; Wang, Ning; Fu, Jingshun; Zhao, Wenhui; Duan, Boqiang; Zhao, Jungui

2018-04-01

High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.

A numerical comparison of discrete Kalman filtering algorithms: An orbit determination case study

NASA Technical Reports Server (NTRS)

Thornton, C. L.; Bierman, G. J.

1976-01-01

The numerical stability and accuracy of various Kalman filter algorithms are thoroughly studied. Numerical results and conclusions are based on a realistic planetary approach orbit determination study. The case study results of this report highlight the numerical instability of the conventional and stabilized Kalman algorithms. Numerical errors associated with these algorithms can be so large as to obscure important mismodeling effects and thus give misleading estimates of filter accuracy. The positive result of this study is that the Bierman-Thornton U-D covariance factorization algorithm is computationally efficient, with CPU costs that differ negligibly from the conventional Kalman costs. In addition, accuracy of the U-D filter using single-precision arithmetic consistently matches the double-precision reference results. Numerical stability of the U-D filter is further demonstrated by its insensitivity of variations in the a priori statistics.

Design and Implementation of Hybrid CORDIC Algorithm Based on Phase Rotation Estimation for NCO

PubMed Central

Zhang, Chaozhu; Han, Jinan; Li, Ke

2014-01-01

The numerical controlled oscillator has wide application in radar, digital receiver, and software radio system. Firstly, this paper introduces the traditional CORDIC algorithm. Then in order to improve computing speed and save resources, this paper proposes a kind of hybrid CORDIC algorithm based on phase rotation estimation applied in numerical controlled oscillator (NCO). Through estimating the direction of part phase rotation, the algorithm reduces part phase rotation and add-subtract unit, so that it decreases delay. Furthermore, the paper simulates and implements the numerical controlled oscillator by Quartus II software and Modelsim software. Finally, simulation results indicate that the improvement over traditional CORDIC algorithm is achieved in terms of ease of computation, resource utilization, and computing speed/delay while maintaining the precision. It is suitable for high speed and precision digital modulation and demodulation. PMID:25110750

Fast forward kinematics algorithm for real-time and high-precision control of the 3-RPS parallel mechanism

NASA Astrophysics Data System (ADS)

Wang, Yue; Yu, Jingjun; Pei, Xu

2018-06-01

A new forward kinematics algorithm for the mechanism of 3-RPS (R: Revolute; P: Prismatic; S: Spherical) parallel manipulators is proposed in this study. This algorithm is primarily based on the special geometric conditions of the 3-RPS parallel mechanism, and it eliminates the errors produced by parasitic motions to improve and ensure accuracy. Specifically, the errors can be less than 10-6. In this method, only the group of solutions that is consistent with the actual situation of the platform is obtained rapidly. This algorithm substantially improves calculation efficiency because the selected initial values are reasonable, and all the formulas in the calculation are analytical. This novel forward kinematics algorithm is well suited for real-time and high-precision control of the 3-RPS parallel mechanism.

Clustering algorithms for identifying core atom sets and for assessing the precision of protein structure ensembles.

PubMed

Snyder, David A; Montelione, Gaetano T

2005-06-01

An important open question in the field of NMR-based biomolecular structure determination is how best to characterize the precision of the resulting ensemble of structures. Typically, the RMSD, as minimized in superimposing the ensemble of structures, is the preferred measure of precision. However, the presence of poorly determined atomic coordinates and multiple "RMSD-stable domains"--locally well-defined regions that are not aligned in global superimpositions--complicate RMSD calculations. In this paper, we present a method, based on a novel, structurally defined order parameter, for identifying a set of core atoms to use in determining superimpositions for RMSD calculations. In addition we present a method for deciding whether to partition that core atom set into "RMSD-stable domains" and, if so, how to determine partitioning of the core atom set. We demonstrate our algorithm and its application in calculating statistically sound RMSD values by applying it to a set of NMR-derived structural ensembles, superimposing each RMSD-stable domain (or the entire core atom set, where appropriate) found in each protein structure under consideration. A parameter calculated by our algorithm using a novel, kurtosis-based criterion, the epsilon-value, is a measure of precision of the superimposition that complements the RMSD. In addition, we compare our algorithm with previously described algorithms for determining core atom sets. The methods presented in this paper for biomolecular structure superimposition are quite general, and have application in many areas of structural bioinformatics and structural biology.

A Mixed Finite Volume Element Method for Flow Calculations in Porous Media

NASA Technical Reports Server (NTRS)

Jones, Jim E.

1996-01-01

A key ingredient in the simulation of flow in porous media is the accurate determination of the velocities that drive the flow. The large scale irregularities of the geology, such as faults, fractures, and layers suggest the use of irregular grids in the simulation. Work has been done in applying the finite volume element (FVE) methodology as developed by McCormick in conjunction with mixed methods which were developed by Raviart and Thomas. The resulting mixed finite volume element discretization scheme has the potential to generate more accurate solutions than standard approaches. The focus of this paper is on a multilevel algorithm for solving the discrete mixed FVE equations. The algorithm uses a standard cell centered finite difference scheme as the 'coarse' level and the more accurate mixed FVE scheme as the 'fine' level. The algorithm appears to have potential as a fast solver for large size simulations of flow in porous media.

Detection of Mixed Infection from Bacterial Whole Genome Sequence Data Allows Assessment of Its Role in Clostridium difficile Transmission

PubMed Central

Eyre, David W.; Cule, Madeleine L.; Griffiths, David; Crook, Derrick W.; Peto, Tim E. A.

2013-01-01

Bacterial whole genome sequencing offers the prospect of rapid and high precision investigation of infectious disease outbreaks. Close genetic relationships between microorganisms isolated from different infected cases suggest transmission is a strong possibility, whereas transmission between cases with genetically distinct bacterial isolates can be excluded. However, undetected mixed infections—infection with ≥2 unrelated strains of the same species where only one is sequenced—potentially impairs exclusion of transmission with certainty, and may therefore limit the utility of this technique. We investigated the problem by developing a computationally efficient method for detecting mixed infection without the need for resource-intensive independent sequencing of multiple bacterial colonies. Given the relatively low density of single nucleotide polymorphisms within bacterial sequence data, direct reconstruction of mixed infection haplotypes from current short-read sequence data is not consistently possible. We therefore use a two-step maximum likelihood-based approach, assuming each sample contains up to two infecting strains. We jointly estimate the proportion of the infection arising from the dominant and minor strains, and the sequence divergence between these strains. In cases where mixed infection is confirmed, the dominant and minor haplotypes are then matched to a database of previously sequenced local isolates. We demonstrate the performance of our algorithm with in silico and in vitro mixed infection experiments, and apply it to transmission of an important healthcare-associated pathogen, Clostridium difficile. Using hospital ward movement data in a previously described stochastic transmission model, 15 pairs of cases enriched for likely transmission events associated with mixed infection were selected. Our method identified four previously undetected mixed infections, and a previously undetected transmission event, but no direct transmission between the pairs of cases under investigation. These results demonstrate that mixed infections can be detected without additional sequencing effort, and this will be important in assessing the extent of cryptic transmission in our hospitals. PMID:23658511

The MHOST finite element program: 3-D inelastic analysis methods for hot section components. Volume 1: Theoretical manual

NASA Technical Reports Server (NTRS)

Nakazawa, Shohei

1991-01-01

Formulations and algorithms implemented in the MHOST finite element program are discussed. The code uses a novel concept of the mixed iterative solution technique for the efficient 3-D computations of turbine engine hot section components. The general framework of variational formulation and solution algorithms are discussed which were derived from the mixed three field Hu-Washizu principle. This formulation enables the use of nodal interpolation for coordinates, displacements, strains, and stresses. Algorithmic description of the mixed iterative method includes variations for the quasi static, transient dynamic and buckling analyses. The global-local analysis procedure referred to as the subelement refinement is developed in the framework of the mixed iterative solution, of which the detail is presented. The numerically integrated isoparametric elements implemented in the framework is discussed. Methods to filter certain parts of strain and project the element discontinuous quantities to the nodes are developed for a family of linear elements. Integration algorithms are described for linear and nonlinear equations included in MHOST program.

Single-channel mixed signal blind source separation algorithm based on multiple ICA processing

NASA Astrophysics Data System (ADS)

Cheng, Xiefeng; Li, Ji

2017-01-01

Take separating the fetal heart sound signal from the mixed signal that get from the electronic stethoscope as the research background, the paper puts forward a single-channel mixed signal blind source separation algorithm based on multiple ICA processing. Firstly, according to the empirical mode decomposition (EMD), the single-channel mixed signal get multiple orthogonal signal components which are processed by ICA. The multiple independent signal components are called independent sub component of the mixed signal. Then by combining with the multiple independent sub component into single-channel mixed signal, the single-channel signal is expanded to multipath signals, which turns the under-determined blind source separation problem into a well-posed blind source separation problem. Further, the estimate signal of source signal is get by doing the ICA processing. Finally, if the separation effect is not very ideal, combined with the last time's separation effect to the single-channel mixed signal, and keep doing the ICA processing for more times until the desired estimated signal of source signal is get. The simulation results show that the algorithm has good separation effect for the single-channel mixed physiological signals.

HIITE: HIV-1 incidence and infection time estimator.

PubMed

Park, Sung Yong; Love, Tanzy M T; Kapoor, Shivankur; Lee, Ha Youn

2018-06-15

Around 2.1 million new HIV-1 infections were reported in 2015, alerting that the HIV-1 epidemic remains a significant global health challenge. Precise incidence assessment strengthens epidemic monitoring efforts and guides strategy optimization for prevention programs. Estimating the onset time of HIV-1 infection can facilitate optimal clinical management and identify key populations largely responsible for epidemic spread and thereby infer HIV-1 transmission chains. Our goal is to develop a genomic assay estimating the incidence and infection time in a single cross-sectional survey setting. We created a web-based platform, HIV-1 incidence and infection time estimator (HIITE), which processes envelope gene sequences using hierarchical clustering algorithms and informs the stage of infection, along with time since infection for incident cases. HIITE's performance was evaluated using 585 incident and 305 chronic specimens' envelope gene sequences collected from global cohorts including HIV-1 vaccine trial participants. HIITE precisely identified chronically infected individuals as being chronic with an error less than 1% and correctly classified 94% of recently infected individuals as being incident. Using a mixed-effect model, an incident specimen's time since infection was estimated from its single lineage diversity, showing 14% prediction error for time since infection. HIITE is the first algorithm to inform two key metrics from a single time point sequence sample. HIITE has the capacity for assessing not only population-level epidemic spread but also individual-level transmission events from a single survey, advancing HIV prevention and intervention programs. Web-based HIITE and source code of HIITE are available at http://www.hayounlee.org/software.html. Supplementary data are available at Bioinformatics online.

Highly efficient classification and identification of human pathogenic bacteria by MALDI-TOF MS.

PubMed

Hsieh, Sen-Yung; Tseng, Chiao-Li; Lee, Yun-Shien; Kuo, An-Jing; Sun, Chien-Feng; Lin, Yen-Hsiu; Chen, Jen-Kun

2008-02-01

Accurate and rapid identification of pathogenic microorganisms is of critical importance in disease treatment and public health. Conventional work flows are time-consuming, and procedures are multifaceted. MS can be an alternative but is limited by low efficiency for amino acid sequencing as well as low reproducibility for spectrum fingerprinting. We systematically analyzed the feasibility of applying MS for rapid and accurate bacterial identification. Directly applying bacterial colonies without further protein extraction to MALDI-TOF MS analysis revealed rich peak contents and high reproducibility. The MS spectra derived from 57 isolates comprising six human pathogenic bacterial species were analyzed using both unsupervised hierarchical clustering and supervised model construction via the Genetic Algorithm. Hierarchical clustering analysis categorized the spectra into six groups precisely corresponding to the six bacterial species. Precise classification was also maintained in an independently prepared set of bacteria even when the numbers of m/z values were reduced to six. In parallel, classification models were constructed via Genetic Algorithm analysis. A model containing 18 m/z values accurately classified independently prepared bacteria and identified those species originally not used for model construction. Moreover bacteria fewer than 10(4) cells and different species in bacterial mixtures were identified using the classification model approach. In conclusion, the application of MALDI-TOF MS in combination with a suitable model construction provides a highly accurate method for bacterial classification and identification. The approach can identify bacteria with low abundance even in mixed flora, suggesting that a rapid and accurate bacterial identification using MS techniques even before culture can be attained in the near future.

Nonlinear unbiased minimum-variance filter for Mars entry autonomous navigation under large uncertainties and unknown measurement bias.

PubMed

Xiao, Mengli; Zhang, Yongbo; Fu, Huimin; Wang, Zhihua

2018-05-01

High-precision navigation algorithm is essential for the future Mars pinpoint landing mission. The unknown inputs caused by large uncertainties of atmospheric density and aerodynamic coefficients as well as unknown measurement biases may cause large estimation errors of conventional Kalman filters. This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation. This filter has been designed to solve this problem by estimating the state and unknown measurement biases simultaneously with derivative-free character, leading to a high-precision algorithm for the Mars entry navigation. IMU/radio beacons integrated navigation is introduced in the simulation, and the result shows that with or without radio blackout, our proposed filter could achieve an accurate state estimation, much better than the conventional unscented Kalman filter, showing the ability of high-precision Mars entry navigation algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

F-MAP: A Bayesian approach to infer the gene regulatory network using external hints

PubMed Central

Shahdoust, Maryam; Mahjub, Hossein; Sadeghi, Mehdi

2017-01-01

The Common topological features of related species gene regulatory networks suggest reconstruction of the network of one species by using the further information from gene expressions profile of related species. We present an algorithm to reconstruct the gene regulatory network named; F-MAP, which applies the knowledge about gene interactions from related species. Our algorithm sets a Bayesian framework to estimate the precision matrix of one species microarray gene expressions dataset to infer the Gaussian Graphical model of the network. The conjugate Wishart prior is used and the information from related species is applied to estimate the hyperparameters of the prior distribution by using the factor analysis. Applying the proposed algorithm on six related species of drosophila shows that the precision of reconstructed networks is improved considerably compared to the precision of networks constructed by other Bayesian approaches. PMID:28938012

Study on application of adaptive fuzzy control and neural network in the automatic leveling system

NASA Astrophysics Data System (ADS)

Xu, Xiping; Zhao, Zizhao; Lan, Weiyong; Sha, Lei; Qian, Cheng

2015-04-01

This paper discusses the adaptive fuzzy control and neural network BP algorithm in large flat automatic leveling control system application. The purpose is to develop a measurement system with a flat quick leveling, Make the installation on the leveling system of measurement with tablet, to be able to achieve a level in precision measurement work quickly, improve the efficiency of the precision measurement. This paper focuses on the automatic leveling system analysis based on fuzzy controller, Use of the method of combining fuzzy controller and BP neural network, using BP algorithm improve the experience rules .Construct an adaptive fuzzy control system. Meanwhile the learning rate of the BP algorithm has also been run-rate adjusted to accelerate convergence. The simulation results show that the proposed control method can effectively improve the leveling precision of automatic leveling system and shorten the time of leveling.

High-precision tracking of brownian boomerang colloidal particles confined in quasi two dimensions.

PubMed

Chakrabarty, Ayan; Wang, Feng; Fan, Chun-Zhen; Sun, Kai; Wei, Qi-Huo

2013-11-26

In this article, we present a high-precision image-processing algorithm for tracking the translational and rotational Brownian motion of boomerang-shaped colloidal particles confined in quasi-two-dimensional geometry. By measuring mean square displacements of an immobilized particle, we demonstrate that the positional and angular precision of our imaging and image-processing system can achieve 13 nm and 0.004 rad, respectively. By analyzing computer-simulated images, we demonstrate that the positional and angular accuracies of our image-processing algorithm can achieve 32 nm and 0.006 rad. Because of zero correlations between the displacements in neighboring time intervals, trajectories of different videos of the same particle can be merged into a very long time trajectory, allowing for long-time averaging of different physical variables. We apply this image-processing algorithm to measure the diffusion coefficients of boomerang particles of three different apex angles and discuss the angle dependence of these diffusion coefficients.

On the precision of automated activation time estimation

NASA Technical Reports Server (NTRS)

Kaplan, D. T.; Smith, J. M.; Rosenbaum, D. S.; Cohen, R. J.

1988-01-01

We examined how the assignment of local activation times in epicardial and endocardial electrograms is affected by sampling rate, ambient signal-to-noise ratio, and sinx/x waveform interpolation. Algorithms used for the estimation of fiducial point locations included dV/dtmax, and a matched filter detection algorithm. Test signals included epicardial and endocardial electrograms overlying both normal and infarcted regions of dog myocardium. Signal-to-noise levels were adjusted by combining known data sets with white noise "colored" to match the spectral characteristics of experimentally recorded noise. For typical signal-to-noise ratios and sampling rates, the template-matching algorithm provided the greatest precision in reproducibly estimating fiducial point location, and sinx/x interpolation allowed for an additional significant improvement. With few restrictions, combining these two techniques may allow for use of digitization rates below the Nyquist rate without significant loss of precision.

New algorithm for lossless hyper-spectral image compression with mixing transform to eliminate redundancy

NASA Astrophysics Data System (ADS)

Xie, ChengJun; Xu, Lin

2008-03-01

This paper presents a new algorithm based on mixing transform to eliminate redundancy, SHIRCT and subtraction mixing transform is used to eliminate spectral redundancy, 2D-CDF(2,2)DWT to eliminate spatial redundancy, This transform has priority in hardware realization convenience, since it can be fully implemented by add and shift operation. Its redundancy elimination effect is better than (1D+2D)CDF(2,2)DWT. Here improved SPIHT+CABAC mixing compression coding algorithm is used to implement compression coding. The experiment results show that in lossless image compression applications the effect of this method is a little better than the result acquired using (1D+2D)CDF(2,2)DWT+improved SPIHT+CABAC, still it is much better than the results acquired by JPEG-LS, WinZip, ARJ, DPCM, the research achievements of a research team of Chinese Academy of Sciences, NMST and MST. Using hyper-spectral image Canal of American JPL laboratory as the data set for lossless compression test, on the average the compression ratio of this algorithm exceeds the above algorithms by 42%,37%,35%,30%,16%,13%,11% respectively.

Optics measurement algorithms and error analysis for the proton energy frontier

NASA Astrophysics Data System (ADS)

Langner, A.; Tomás, R.

2015-03-01

Optics measurement algorithms have been improved in preparation for the commissioning of the LHC at higher energy, i.e., with an increased damage potential. Due to machine protection considerations the higher energy sets tighter limits in the maximum excitation amplitude and the total beam charge, reducing the signal to noise ratio of optics measurements. Furthermore the precision in 2012 (4 TeV) was insufficient to understand beam size measurements and determine interaction point (IP) β -functions (β*). A new, more sophisticated algorithm has been developed which takes into account both the statistical and systematic errors involved in this measurement. This makes it possible to combine more beam position monitor measurements for deriving the optical parameters and demonstrates to significantly improve the accuracy and precision. Measurements from the 2012 run have been reanalyzed which, due to the improved algorithms, result in a significantly higher precision of the derived optical parameters and decreased the average error bars by a factor of three to four. This allowed the calculation of β* values and demonstrated to be fundamental in the understanding of emittance evolution during the energy ramp.

Three-dimensional high-precision indoor positioning strategy using Tabu search based on visible light communication

NASA Astrophysics Data System (ADS)

Peng, Qi; Guan, Weipeng; Wu, Yuxiang; Cai, Ye; Xie, Canyu; Wang, Pengfei

2018-01-01

This paper proposes a three-dimensional (3-D) high-precision indoor positioning strategy using Tabu search based on visible light communication. Tabu search is a powerful global optimization algorithm, and the 3-D indoor positioning can be transformed into an optimal solution problem. Therefore, in the 3-D indoor positioning, the optimal receiver coordinate can be obtained by the Tabu search algorithm. For all we know, this is the first time the Tabu search algorithm is applied to visible light positioning. Each light-emitting diode (LED) in the system broadcasts a unique identity (ID) and transmits the ID information. When the receiver detects optical signals with ID information from different LEDs, using the global optimization of the Tabu search algorithm, the 3-D high-precision indoor positioning can be realized when the fitness value meets certain conditions. Simulation results show that the average positioning error is 0.79 cm, and the maximum error is 5.88 cm. The extended experiment of trajectory tracking also shows that 95.05% positioning errors are below 1.428 cm. It can be concluded from the data that the 3-D indoor positioning based on the Tabu search algorithm achieves the requirements of centimeter level indoor positioning. The algorithm used in indoor positioning is very effective and practical and is superior to other existing methods for visible light indoor positioning.

Simultaneous Mass Determination for Gravitationally Coupled Asteroids

NASA Astrophysics Data System (ADS)

Baer, James; Chesley, Steven R.

2017-08-01

The conventional least-squares asteroid mass determination algorithm allows us to solve for the mass of a large subject asteroid that is perturbing the trajectory of a smaller test asteroid. However, this algorithm is necessarily a first approximation, ignoring the possibility that the subject asteroid may itself be perturbed by the test asteroid, or that the encounter’s precise geometry may be entangled with encounters involving other asteroids. After reviewing the conventional algorithm, we use it to calculate the masses of 30 main-belt asteroids. Compared to our previous results, we find new mass estimates for eight asteroids (11 Parthenope, 27 Euterpe, 51 Neimausa, 76 Freia, 121 Hermione, 324 Bamberga, 476 Hedwig, and 532 Herculina) and significantly more precise estimates for six others (2 Pallas, 3 Juno, 4 Vesta, 9 Metis, 16 Psyche, and 88 Thisbe). However, we also find that the conventional algorithm yields questionable results in several gravitationally coupled cases. To address such cases, we describe a new algorithm that allows the epoch state vectors of the subject asteroids to be included as solve-for parameters, allowing for the simultaneous solution of the masses and epoch state vectors of multiple subject and test asteroids. We then apply this algorithm to the same 30 main-belt asteroids and conclude that mass determinations resulting from current and future high-precision astrometric sources (such as Gaia) should conduct a thorough search for possible gravitational couplings and account for their effects.

Efficient Boundary Extraction of BSP Solids Based on Clipping Operations.

PubMed

Wang, Charlie C L; Manocha, Dinesh

2013-01-01

We present an efficient algorithm to extract the manifold surface that approximates the boundary of a solid represented by a Binary Space Partition (BSP) tree. Our polygonization algorithm repeatedly performs clipping operations on volumetric cells that correspond to a spatial convex partition and computes the boundary by traversing the connected cells. We use point-based representations along with finite-precision arithmetic to improve the efficiency and generate the B-rep approximation of a BSP solid. The core of our polygonization method is a novel clipping algorithm that uses a set of logical operations to make it resistant to degeneracies resulting from limited precision of floating-point arithmetic. The overall BSP to B-rep conversion algorithm can accurately generate boundaries with sharp and small features, and is faster than prior methods. At the end of this paper, we use this algorithm for a few geometric processing applications including Boolean operations, model repair, and mesh reconstruction.

An improved wavelet neural network medical image segmentation algorithm with combined maximum entropy

NASA Astrophysics Data System (ADS)

Hu, Xiaoqian; Tao, Jinxu; Ye, Zhongfu; Qiu, Bensheng; Xu, Jinzhang

2018-05-01

In order to solve the problem of medical image segmentation, a wavelet neural network medical image segmentation algorithm based on combined maximum entropy criterion is proposed. Firstly, we use bee colony algorithm to optimize the network parameters of wavelet neural network, get the parameters of network structure, initial weights and threshold values, and so on, we can quickly converge to higher precision when training, and avoid to falling into relative extremum; then the optimal number of iterations is obtained by calculating the maximum entropy of the segmented image, so as to achieve the automatic and accurate segmentation effect. Medical image segmentation experiments show that the proposed algorithm can reduce sample training time effectively and improve convergence precision, and segmentation effect is more accurate and effective than traditional BP neural network (back propagation neural network : a multilayer feed forward neural network which trained according to the error backward propagation algorithm.

Data-driven gradient algorithm for high-precision quantum control

NASA Astrophysics Data System (ADS)

Wu, Re-Bing; Chu, Bing; Owens, David H.; Rabitz, Herschel

2018-04-01

In the quest to achieve scalable quantum information processing technologies, gradient-based optimal control algorithms (e.g., grape) are broadly used for implementing high-precision quantum gates, but their performance is often hindered by deterministic or random errors in the system model and the control electronics. In this paper, we show that grape can be taught to be more effective by jointly learning from the design model and the experimental data obtained from process tomography. The resulting data-driven gradient optimization algorithm (d-grape) can in principle correct all deterministic gate errors, with a mild efficiency loss. The d-grape algorithm may become more powerful with broadband controls that involve a large number of control parameters, while other algorithms usually slow down due to the increased size of the search space. These advantages are demonstrated by simulating the implementation of a two-qubit controlled-not gate.

Formal verification of a fault tolerant clock synchronization algorithm

NASA Technical Reports Server (NTRS)

Rushby, John; Vonhenke, Frieder

1989-01-01

A formal specification and mechanically assisted verification of the interactive convergence clock synchronization algorithm of Lamport and Melliar-Smith is described. Several technical flaws in the analysis given by Lamport and Melliar-Smith were discovered, even though their presentation is unusally precise and detailed. It seems that these flaws were not detected by informal peer scrutiny. The flaws are discussed and a revised presentation of the analysis is given that not only corrects the flaws but is also more precise and easier to follow. Some of the corrections to the flaws require slight modifications to the original assumptions underlying the algorithm and to the constraints on its parameters, and thus change the external specifications of the algorithm. The formal analysis of the interactive convergence clock synchronization algorithm was performed using the Enhanced Hierarchical Development Methodology (EHDM) formal specification and verification environment. This application of EHDM provides a demonstration of some of the capabilities of the system.

Operations research applications in nuclear energy

NASA Astrophysics Data System (ADS)

Johnson, Benjamin Lloyd

This dissertation consists of three papers; the first is published in Annals of Operations Research, the second is nearing submission to INFORMS Journal on Computing, and the third is the predecessor of a paper nearing submission to Progress in Nuclear Energy. We apply operations research techniques to nuclear waste disposal and nuclear safeguards. Although these fields are different, they allow us to showcase some benefits of using operations research techniques to enhance nuclear energy applications. The first paper, "Optimizing High-Level Nuclear Waste Disposal within a Deep Geologic Repository," presents a mixed-integer programming model that determines where to place high-level nuclear waste packages in a deep geologic repository to minimize heat load concentration. We develop a heuristic that increases the size of solvable model instances. The second paper, "Optimally Configuring a Measurement System to Detect Diversions from a Nuclear Fuel Cycle," introduces a simulation-optimization algorithm and an integer-programming model to find the best, or near-best, resource-limited nuclear fuel cycle measurement system with a high degree of confidence. Given location-dependent measurement method precisions, we (i) optimize the configuration of n methods at n locations of a hypothetical nuclear fuel cycle facility, (ii) find the most important location at which to improve method precision, and (iii) determine the effect of measurement frequency on near-optimal configurations and objective values. Our results correspond to existing outcomes but we obtain them at least an order of magnitude faster. The third paper, "Optimizing Nuclear Material Control and Accountability Measurement Systems," extends the integer program from the second paper to locate measurement methods in a larger, hypothetical nuclear fuel cycle scenario given fixed purchase and utilization budgets. This paper also presents two mixed-integer quadratic programming models to increase the precision of existing methods given a fixed improvement budget and to reduce the measurement uncertainty in the system while limiting improvement costs. We quickly obtain similar or better solutions compared to several intuitive analyses that take much longer to perform.

Quantum algorithms for Gibbs sampling and hitting-time estimation

DOE PAGES

Chowdhury, Anirban Narayan; Somma, Rolando D.

2017-02-01

In this paper, we present quantum algorithms for solving two problems regarding stochastic processes. The first algorithm prepares the thermal Gibbs state of a quantum system and runs in time almost linear in √Nβ/Ζ and polynomial in log(1/ϵ), where N is the Hilbert space dimension, β is the inverse temperature, Ζ is the partition function, and ϵ is the desired precision of the output state. Our quantum algorithm exponentially improves the dependence on 1/ϵ and quadratically improves the dependence on β of known quantum algorithms for this problem. The second algorithm estimates the hitting time of a Markov chain. Formore » a sparse stochastic matrix Ρ, it runs in time almost linear in 1/(ϵΔ 3/2), where ϵ is the absolute precision in the estimation and Δ is a parameter determined by Ρ, and whose inverse is an upper bound of the hitting time. Our quantum algorithm quadratically improves the dependence on 1/ϵ and 1/Δ of the analog classical algorithm for hitting-time estimation. Finally, both algorithms use tools recently developed in the context of Hamiltonian simulation, spectral gap amplification, and solving linear systems of equations.« less

Application of square-root filtering for spacecraft attitude control

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Schmidt, S. F.; Goka, T.

1978-01-01

Suitable digital algorithms are developed and tested for providing on-board precision attitude estimation and pointing control for potential use in the Landsat-D spacecraft. These algorithms provide pointing accuracy of better than 0.01 deg. To obtain necessary precision with efficient software, a six state-variable square-root Kalman filter combines two star tracker measurements to update attitude estimates obtained from processing three gyro outputs. The validity of the estimation and control algorithms are established, and the sensitivity of their performance to various error sources and software parameters are investigated by detailed digital simulation. Spacecraft computer memory, cycle time, and accuracy requirements are estimated.

A pruning algorithm for Meta-blocking based on cumulative weight

NASA Astrophysics Data System (ADS)

Zhang, Fulin; Gao, Zhipeng; Niu, Kun

2017-08-01

Entity Resolution is an important process in data cleaning and data integration. It usually employs a blocking method to avoid the quadratic complexity work when scales to large data sets. Meta-blocking can perform better in the context of highly heterogeneous information spaces. Yet, its precision and efficiency still have room to improve. In this paper, we present a new pruning algorithm for Meta-Blocking. It can achieve a higher precision than the existing WEP algorithm at a small cost of recall. In addition, can reduce the runtime of the blocking process. We evaluate our proposed method over five real-world data sets.

Forecasting Nonlinear Chaotic Time Series with Function Expression Method Based on an Improved Genetic-Simulated Annealing Algorithm

PubMed Central

Wang, Jun; Zhou, Bi-hua; Zhou, Shu-dao; Sheng, Zheng

2015-01-01

The paper proposes a novel function expression method to forecast chaotic time series, using an improved genetic-simulated annealing (IGSA) algorithm to establish the optimum function expression that describes the behavior of time series. In order to deal with the weakness associated with the genetic algorithm, the proposed algorithm incorporates the simulated annealing operation which has the strong local search ability into the genetic algorithm to enhance the performance of optimization; besides, the fitness function and genetic operators are also improved. Finally, the method is applied to the chaotic time series of Quadratic and Rossler maps for validation. The effect of noise in the chaotic time series is also studied numerically. The numerical results verify that the method can forecast chaotic time series with high precision and effectiveness, and the forecasting precision with certain noise is also satisfactory. It can be concluded that the IGSA algorithm is energy-efficient and superior. PMID:26000011

Forecasting nonlinear chaotic time series with function expression method based on an improved genetic-simulated annealing algorithm.

PubMed

Wang, Jun; Zhou, Bi-hua; Zhou, Shu-dao; Sheng, Zheng

2015-01-01

The paper proposes a novel function expression method to forecast chaotic time series, using an improved genetic-simulated annealing (IGSA) algorithm to establish the optimum function expression that describes the behavior of time series. In order to deal with the weakness associated with the genetic algorithm, the proposed algorithm incorporates the simulated annealing operation which has the strong local search ability into the genetic algorithm to enhance the performance of optimization; besides, the fitness function and genetic operators are also improved. Finally, the method is applied to the chaotic time series of Quadratic and Rossler maps for validation. The effect of noise in the chaotic time series is also studied numerically. The numerical results verify that the method can forecast chaotic time series with high precision and effectiveness, and the forecasting precision with certain noise is also satisfactory. It can be concluded that the IGSA algorithm is energy-efficient and superior.

Old and new techniques mixed up into optical photomask measurement method

NASA Astrophysics Data System (ADS)

Fukui, Jumpei; Tachibana, Yusaku; Osanai, Makoto

2017-07-01

It has been still highly required for cost efficient solution with easy operation for full-automated CD measurement for line width about 500nm up to 5μm on photomask, because it is frequently use such photomask in the process of manufacturing MEMS sensor for IoT and some devices made in BCD (Bipola CMOS DMOS). As reply to such demand in photomask manufacturing field, we try to take a low noise digital camera technology and LED light source for i-line, which are recently developed, into new measuring tool in order to achieve 1nm (3σ) repeatability for line width measurement between 300nm to 10μm. In addition, for the purpose of full-automated operation, it is very important to find where an initial target line in dense pattern. To achieve such auto line detection precisely, we have improved accuracy of high precision stage (20nm as 3σ) and an alignment algorithm of MEMS Stepper to combine with this tool. As for user-friendly interface, Windows based software helps a lot for not only the operation but also recipe creation or edition in Excel. Actually, in the MEMS manufacturing process, there are various photomasks which need to be check and measure frequently therefore various recipe files are also have to be created and edited frequently.. In order to meet such a requirement in photomask management, we try to make it true by mixing old and new techniques together into one system, which comes to fully automated and cost efficient tool with 1nm repeatability in CD measurement.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Sixth Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2015-01-01

This paper presents an overview of the sixth revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This algorithm is referred to as the Airborne Spacing for Terminal Arrival Routes version 13 (ASTAR13). This airborne self-spacing concept contains both trajectory-based and state-based mechanisms for calculating the speeds required to achieve or maintain a precise spacing interval. The trajectory-based capability allows for spacing operations prior to the aircraft being on a common path. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm adds the state-based capability in support of evolving industry standards relating to airborne self-spacing.

Lossless compression of image data products on th e FIFE CD-ROM series

NASA Technical Reports Server (NTRS)

Newcomer, Jeffrey A.; Strebel, Donald E.

1993-01-01

How do you store enough of the key data sets, from a total of 120 gigabytes of data collected for a scientific experiment, on a collection of CD-ROM's, small enough to distribute to a broad scientific community? In such an application where information loss in unacceptable, lossless compression algorithms are the only choice. Although lossy compression algorithms can provide an order of magnitude improvement in compression ratios over lossless algorithms the information that is lost is often part of the key scientific precision of the data. Therefore, lossless compression algorithms are and will continue to be extremely important in minimizing archiving storage requirements and distribution of large earth and space (ESS) data sets while preserving the essential scientific precision of the data.

The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparative validation of GHG-CCI SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT CO2 and CH4 retrieval algorithm products with measurements from the TCCON

NASA Astrophysics Data System (ADS)

Dils, B.; Buchwitz, M.; Reuter, M.; Schneising, O.; Boesch, H.; Parker, R.; Guerlet, S.; Aben, I.; Blumenstock, T.; Burrows, J. P.; Butz, A.; Deutscher, N. M.; Frankenberg, C.; Hase, F.; Hasekamp, O. P.; Heymann, J.; De Mazière, M.; Notholt, J.; Sussmann, R.; Warneke, T.; Griffith, D.; Sherlock, V.; Wunch, D.

2014-06-01

Column-averaged dry-air mole fractions of carbon dioxide and methane have been retrieved from spectra acquired by the TANSO-FTS (Thermal And Near-infrared Sensor for carbon Observations-Fourier Transform Spectrometer) and SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography) instruments on board GOSAT (Greenhouse gases Observing SATellite) and ENVISAT (ENVIronmental SATellite), respectively, using a range of European retrieval algorithms. These retrievals have been compared with data from ground-based high-resolution Fourier transform spectrometers (FTSs) from the Total Carbon Column Observing Network (TCCON). The participating algorithms are the weighting function modified differential optical absorption spectroscopy (DOAS) algorithm (WFMD, University of Bremen), the Bremen optimal estimation DOAS algorithm (BESD, University of Bremen), the iterative maximum a posteriori DOAS (IMAP, Jet Propulsion Laboratory (JPL) and Netherlands Institute for Space Research algorithm (SRON)), the proxy and full-physics versions of SRON's RemoTeC algorithm (SRPR and SRFP, respectively) and the proxy and full-physics versions of the University of Leicester's adaptation of the OCO (Orbiting Carbon Observatory) algorithm (OCPR and OCFP, respectively). The goal of this algorithm inter-comparison was to identify strengths and weaknesses of the various so-called round- robin data sets generated with the various algorithms so as to determine which of the competing algorithms would proceed to the next round of the European Space Agency's (ESA) Greenhouse Gas Climate Change Initiative (GHG-CCI) project, which is the generation of the so-called Climate Research Data Package (CRDP), which is the first version of the Essential Climate Variable (ECV) "greenhouse gases" (GHGs). For XCO2, all algorithms reach the precision requirements for inverse modelling (< 8 ppm), with only WFMD having a lower precision (4.7 ppm) than the other algorithm products (2.4-2.5 ppm). When looking at the seasonal relative accuracy (SRA, variability of the bias in space and time), none of the algorithms have reached the demanding < 0.5 ppm threshold. For XCH4, the precision for both SCIAMACHY products (50.2 ppb for IMAP and 76.4 ppb for WFMD) fails to meet the < 34 ppb threshold for inverse modelling, but note that this work focusses on the period after the 2005 SCIAMACHY detector degradation. The GOSAT XCH4 precision ranges between 18.1 and 14.0 ppb. Looking at the SRA, all GOSAT algorithm products reach the < 10 ppm threshold (values ranging between 5.4 and 6.2 ppb). For SCIAMACHY, IMAP and WFMD have a SRA of 17.2 and 10.5 ppb, respectively.

Bit-level plane image encryption based on coupled map lattice with time-varying delay

NASA Astrophysics Data System (ADS)

Lv, Xiupin; Liao, Xiaofeng; Yang, Bo

2018-04-01

Most of the existing image encryption algorithms had two basic properties: confusion and diffusion in a pixel-level plane based on various chaotic systems. Actually, permutation in a pixel-level plane could not change the statistical characteristics of an image, and many of the existing color image encryption schemes utilized the same method to encrypt R, G and B components, which means that the three color components of a color image are processed three times independently. Additionally, dynamical performance of a single chaotic system degrades greatly with finite precisions in computer simulations. In this paper, a novel coupled map lattice with time-varying delay therefore is applied in color images bit-level plane encryption to solve the above issues. Spatiotemporal chaotic system with both much longer period in digitalization and much excellent performances in cryptography is recommended. Time-varying delay embedded in coupled map lattice enhances dynamical behaviors of the system. Bit-level plane image encryption algorithm has greatly reduced the statistical characteristics of an image through the scrambling processing. The R, G and B components cross and mix with one another, which reduces the correlation among the three components. Finally, simulations are carried out and all the experimental results illustrate that the proposed image encryption algorithm is highly secure, and at the same time, also demonstrates superior performance.

Enhanced detection and visualization of anomalies in spectral imagery

NASA Astrophysics Data System (ADS)

Basener, William F.; Messinger, David W.

2009-05-01

Anomaly detection algorithms applied to hyperspectral imagery are able to reliably identify man-made objects from a natural environment based on statistical/geometric likelyhood. The process is more robust than target identification, which requires precise prior knowledge of the object of interest, but has an inherently higher false alarm rate. Standard anomaly detection algorithms measure deviation of pixel spectra from a parametric model (either statistical or linear mixing) estimating the image background. The topological anomaly detector (TAD) creates a fully non-parametric, graph theory-based, topological model of the image background and measures deviation from this background using codensity. In this paper we present a large-scale comparative test of TAD against 80+ targets in four full HYDICE images using the entire canonical target set for generation of ROC curves. TAD will be compared against several statistics-based detectors including local RX and subspace RX. Even a perfect anomaly detection algorithm would have a high practical false alarm rate in most scenes simply because the user/analyst is not interested in every anomalous object. To assist the analyst in identifying and sorting objects of interest, we investigate coloring of the anomalies with principle components projections using statistics computed from the anomalies. This gives a very useful colorization of anomalies in which objects of similar material tend to have the same color, enabling an analyst to quickly sort and identify anomalies of highest interest.

A novel algorithm for a precise analysis of subchondral bone alterations

PubMed Central

Gao, Liang; Orth, Patrick; Goebel, Lars K. H.; Cucchiarini, Magali; Madry, Henning

2016-01-01

Subchondral bone alterations are emerging as considerable clinical problems associated with articular cartilage repair. Their analysis exposes a pattern of variable changes, including intra-lesional osteophytes, residual microfracture holes, peri-hole bone resorption, and subchondral bone cysts. A precise distinction between them is becoming increasingly important. Here, we present a tailored algorithm based on continuous data to analyse subchondral bone changes using micro-CT images, allowing for a clear definition of each entity. We evaluated this algorithm using data sets originating from two large animal models of osteochondral repair. Intra-lesional osteophytes were detected in 3 of 10 defects in the minipig and in 4 of 5 defects in the sheep model. Peri-hole bone resorption was found in 22 of 30 microfracture holes in the minipig and in 17 of 30 microfracture holes in the sheep model. Subchondral bone cysts appeared in 1 microfracture hole in the minipig and in 5 microfracture holes in the sheep model (n = 30 holes each). Calculation of inter-rater agreement (90% agreement) and Cohen’s kappa (kappa = 0.874) revealed that the novel algorithm is highly reliable, reproducible, and valid. Comparison analysis with the best existing semi-quantitative evaluation method was also performed, supporting the enhanced precision of this algorithm. PMID:27596562

Comparative Study on a Solving Model and Algorithm for a Flush Air Data Sensing System

PubMed Central

Liu, Yanbin; Xiao, Dibo; Lu, Yuping

2014-01-01

With the development of high-performance aircraft, precise air data are necessary to complete challenging tasks such as flight maneuvering with large angles of attack and high speed. As a result, the flush air data sensing system (FADS) was developed to satisfy the stricter control demands. In this paper, comparative stuides on the solving model and algorithm for FADS are conducted. First, the basic principles of FADS are given to elucidate the nonlinear relations between the inputs and the outputs. Then, several different solving models and algorithms of FADS are provided to compute the air data, including the angle of attck, sideslip angle, dynamic pressure and static pressure. Afterwards, the evaluation criteria of the resulting models and algorithms are discussed to satisfy the real design demands. Futhermore, a simulation using these algorithms is performed to identify the properites of the distinct models and algorithms such as the measuring precision and real-time features. The advantages of these models and algorithms corresponding to the different flight conditions are also analyzed, furthermore, some suggestions on their engineering applications are proposed to help future research. PMID:24859025

Comparative study on a solving model and algorithm for a flush air data sensing system.

PubMed

Liu, Yanbin; Xiao, Dibo; Lu, Yuping

2014-05-23

With the development of high-performance aircraft, precise air data are necessary to complete challenging tasks such as flight maneuvering with large angles of attack and high speed. As a result, the flush air data sensing system (FADS) was developed to satisfy the stricter control demands. In this paper, comparative stuides on the solving model and algorithm for FADS are conducted. First, the basic principles of FADS are given to elucidate the nonlinear relations between the inputs and the outputs. Then, several different solving models and algorithms of FADS are provided to compute the air data, including the angle of attck, sideslip angle, dynamic pressure and static pressure. Afterwards, the evaluation criteria of the resulting models and algorithms are discussed to satisfy the real design demands. Futhermore, a simulation using these algorithms is performed to identify the properites of the distinct models and algorithms such as the measuring precision and real-time features. The advantages of these models and algorithms corresponding to the different flight conditions are also analyzed, furthermore, some suggestions on their engineering applications are proposed to help future research.

Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA

PubMed Central

Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari

2014-01-01

A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962

Study on fluorescence spectra of thiamine, riboflavin and pyridoxine

NASA Astrophysics Data System (ADS)

Yang, Hui; Xiao, Xue; Zhao, Xuesong; Hu, Lan; Lv, Caofang; Yin, Zhangkun

2016-01-01

This paper presents the intrinsic fluorescence characteristics of vitamin B1, B2 and B6 measured with 3D fluorescence Spectrophotometer. Three strong fluorescence areas of vitamin B2 locate at λex/λem=270/525nm, 370/525nm and 450/525nm, one fluorescence areas of vitamin B1 locates at λex/λem=370/460nm, two fluorescence areas of vitamin B6 locate at λex/λem=250/370nm and 325/370nm were found. The influence of pH of solution to the fluorescence profile was also discussed. Using the PARAFAC algorithm, 10 vitamin B1, B2 and B6 mixed solutions were successfully decomposed, and the emission profiles, excitation profiles, central wavelengths and the concentration of the three components were retrieved precisely through about 5 iteration times.

Study of nanometer-level precise phase-shift system used in electronic speckle shearography and phase-shift pattern interferometry

NASA Astrophysics Data System (ADS)

Jing, Chao; Liu, Zhongling; Zhou, Ge; Zhang, Yimo

2011-11-01

The nanometer-level precise phase-shift system is designed to realize the phase-shift interferometry in electronic speckle shearography pattern interferometry. The PZT is used as driving component of phase-shift system and translation component of flexure hinge is developed to realize micro displacement of non-friction and non-clearance. Closed-loop control system is designed for high-precision micro displacement, in which embedded digital control system is developed for completing control algorithm and capacitive sensor is used as feedback part for measuring micro displacement in real time. Dynamic model and control model of the nanometer-level precise phase-shift system is analyzed, and high-precision micro displacement is realized with digital PID control algorithm on this basis. It is proved with experiments that the location precision of the precise phase-shift system to step signal of displacement is less than 2nm and the location precision to continuous signal of displacement is less than 5nm, which is satisfied with the request of the electronic speckle shearography and phase-shift pattern interferometry. The stripe images of four-step phase-shift interferometry and the final phase distributed image correlated with distortion of objects are listed in this paper to prove the validity of nanometer-level precise phase-shift system.

A Polynomial Time, Numerically Stable Integer Relation Algorithm

NASA Technical Reports Server (NTRS)

Ferguson, Helaman R. P.; Bailey, Daivd H.; Kutler, Paul (Technical Monitor)

1998-01-01

Let x = (x1, x2...,xn be a vector of real numbers. X is said to possess an integer relation if there exist integers a(sub i) not all zero such that a1x1 + a2x2 + ... a(sub n)Xn = 0. Beginning in 1977 several algorithms (with proofs) have been discovered to recover the a(sub i) given x. The most efficient of these existing integer relation algorithms (in terms of run time and the precision required of the input) has the drawback of being very unstable numerically. It often requires a numeric precision level in the thousands of digits to reliably recover relations in modest-sized test problems. We present here a new algorithm for finding integer relations, which we have named the "PSLQ" algorithm. It is proved in this paper that the PSLQ algorithm terminates with a relation in a number of iterations that is bounded by a polynomial in it. Because this algorithm employs a numerically stable matrix reduction procedure, it is free from the numerical difficulties, that plague other integer relation algorithms. Furthermore, its stability admits an efficient implementation with lower run times oil average than other algorithms currently in Use. Finally, this stability can be used to prove that relation bounds obtained from computer runs using this algorithm are numerically accurate.

A 100-Year Review: Methods and impact of genetic selection in dairy cattle-From daughter-dam comparisons to deep learning algorithms.

PubMed

Weigel, K A; VanRaden, P M; Norman, H D; Grosu, H

2017-12-01

In the early 1900s, breed society herdbooks had been established and milk-recording programs were in their infancy. Farmers wanted to improve the productivity of their cattle, but the foundations of population genetics, quantitative genetics, and animal breeding had not been laid. Early animal breeders struggled to identify genetically superior families using performance records that were influenced by local environmental conditions and herd-specific management practices. Daughter-dam comparisons were used for more than 30 yr and, although genetic progress was minimal, the attention given to performance recording, genetic theory, and statistical methods paid off in future years. Contemporary (herdmate) comparison methods allowed more accurate accounting for environmental factors and genetic progress began to accelerate when these methods were coupled with artificial insemination and progeny testing. Advances in computing facilitated the implementation of mixed linear models that used pedigree and performance data optimally and enabled accurate selection decisions. Sequencing of the bovine genome led to a revolution in dairy cattle breeding, and the pace of scientific discovery and genetic progress accelerated rapidly. Pedigree-based models have given way to whole-genome prediction, and Bayesian regression models and machine learning algorithms have joined mixed linear models in the toolbox of modern animal breeders. Future developments will likely include elucidation of the mechanisms of genetic inheritance and epigenetic modification in key biological pathways, and genomic data will be used with data from on-farm sensors to facilitate precision management on modern dairy farms. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Final Report---Optimization Under Nonconvexity and Uncertainty: Algorithms and Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeff Linderoth

2011-11-06

the goal of this work was to develop new algorithmic techniques for solving large-scale numerical optimization problems, focusing on problems classes that have proven to be among the most challenging for practitioners: those involving uncertainty and those involving nonconvexity. This research advanced the state-of-the-art in solving mixed integer linear programs containing symmetry, mixed integer nonlinear programs, and stochastic optimization problems. The focus of the work done in the continuation was on Mixed Integer Nonlinear Programs (MINLP)s and Mixed Integer Linear Programs (MILP)s, especially those containing a great deal of symmetry.

NVU dynamics. I. Geodesic motion on the constant-potential-energy hypersurface.

PubMed

Ingebrigtsen, Trond S; Toxvaerd, Søren; Heilmann, Ole J; Schrøder, Thomas B; Dyre, Jeppe C

2011-09-14

An algorithm is derived for computer simulation of geodesics on the constant-potential-energy hypersurface of a system of N classical particles. First, a basic time-reversible geodesic algorithm is derived by discretizing the geodesic stationarity condition and implementing the constant-potential-energy constraint via standard Lagrangian multipliers. The basic NVU algorithm is tested by single-precision computer simulations of the Lennard-Jones liquid. Excellent numerical stability is obtained if the force cutoff is smoothed and the two initial configurations have identical potential energy within machine precision. Nevertheless, just as for NVE algorithms, stabilizers are needed for very long runs in order to compensate for the accumulation of numerical errors that eventually lead to "entropic drift" of the potential energy towards higher values. A modification of the basic NVU algorithm is introduced that ensures potential-energy and step-length conservation; center-of-mass drift is also eliminated. Analytical arguments confirmed by simulations demonstrate that the modified NVU algorithm is absolutely stable. Finally, we present simulations showing that the NVU algorithm and the standard leap-frog NVE algorithm have identical radial distribution functions for the Lennard-Jones liquid. © 2011 American Institute of Physics

Instrument-induced spatial crosstalk deconvolution algorithm

NASA Technical Reports Server (NTRS)

Wright, Valerie G.; Evans, Nathan L., Jr.

1986-01-01

An algorithm has been developed which reduces the effects of (deconvolves) instrument-induced spatial crosstalk in satellite image data by several orders of magnitude where highly precise radiometry is required. The algorithm is based upon radiance transfer ratios which are defined as the fractional bilateral exchange of energy betwen pixels A and B.

A Kind of Nonlinear Programming Problem Based on Mixed Fuzzy Relation Equations Constraints

NASA Astrophysics Data System (ADS)

Li, Jinquan; Feng, Shuang; Mi, Honghai

In this work, a kind of nonlinear programming problem with non-differential objective function and under the constraints expressed by a system of mixed fuzzy relation equations is investigated. First, some properties of this kind of optimization problem are obtained. Then, a polynomial-time algorithm for this kind of optimization problem is proposed based on these properties. Furthermore, we show that this algorithm is optimal for the considered optimization problem in this paper. Finally, numerical examples are provided to illustrate our algorithms.

Three-dimensional forward modeling of DC resistivity using the aggregation-based algebraic multigrid method

NASA Astrophysics Data System (ADS)

Chen, Hui; Deng, Ju-Zhi; Yin, Min; Yin, Chang-Chun; Tang, Wen-Wu

2017-03-01

To speed up three-dimensional (3D) DC resistivity modeling, we present a new multigrid method, the aggregation-based algebraic multigrid method (AGMG). We first discretize the differential equation of the secondary potential field with mixed boundary conditions by using a seven-point finite-difference method to obtain a large sparse system of linear equations. Then, we introduce the theory behind the pairwise aggregation algorithms for AGMG and use the conjugate-gradient method with the V-cycle AGMG preconditioner (AGMG-CG) to solve the linear equations. We use typical geoelectrical models to test the proposed AGMG-CG method and compare the results with analytical solutions and the 3DDCXH algorithm for 3D DC modeling (3DDCXH). In addition, we apply the AGMG-CG method to different grid sizes and geoelectrical models and compare it to different iterative methods, such as ILU-BICGSTAB, ILU-GCR, and SSOR-CG. The AGMG-CG method yields nearly linearly decreasing errors, whereas the number of iterations increases slowly with increasing grid size. The AGMG-CG method is precise and converges fast, and thus can improve the computational efficiency in forward modeling of three-dimensional DC resistivity.

An Integrated Vision-Based System for Spacecraft Attitude and Topology Determination for Formation Flight Missions

NASA Technical Reports Server (NTRS)

Rogers, Aaron; Anderson, Kalle; Mracek, Anna; Zenick, Ray

2004-01-01

With the space industry's increasing focus upon multi-spacecraft formation flight missions, the ability to precisely determine system topology and the orientation of member spacecraft relative to both inertial space and each other is becoming a critical design requirement. Topology determination in satellite systems has traditionally made use of GPS or ground uplink position data for low Earth orbits, or, alternatively, inter-satellite ranging between all formation pairs. While these techniques work, they are not ideal for extension to interplanetary missions or to large fleets of decentralized, mixed-function spacecraft. The Vision-Based Attitude and Formation Determination System (VBAFDS) represents a novel solution to both the navigation and topology determination problems with an integrated approach that combines a miniature star tracker with a suite of robust processing algorithms. By combining a single range measurement with vision data to resolve complete system topology, the VBAFDS design represents a simple, resource-efficient solution that is not constrained to certain Earth orbits or formation geometries. In this paper, analysis and design of the VBAFDS integrated guidance, navigation and control (GN&C) technology will be discussed, including hardware requirements, algorithm development, and simulation results in the context of potential mission applications.

Quantifying Auditory Temporal Stability in a Large Database of Recorded Music

PubMed Central

Ellis, Robert J.; Duan, Zhiyan; Wang, Ye

2014-01-01

“Moving to the beat” is both one of the most basic and one of the most profound means by which humans (and a few other species) interact with music. Computer algorithms that detect the precise temporal location of beats (i.e., pulses of musical “energy”) in recorded music have important practical applications, such as the creation of playlists with a particular tempo for rehabilitation (e.g., rhythmic gait training), exercise (e.g., jogging), or entertainment (e.g., continuous dance mixes). Although several such algorithms return simple point estimates of an audio file’s temporal structure (e.g., “average tempo”, “time signature”), none has sought to quantify the temporal stability of a series of detected beats. Such a method-a “Balanced Evaluation of Auditory Temporal Stability” (BEATS)–is proposed here, and is illustrated using the Million Song Dataset (a collection of audio features and music metadata for nearly one million audio files). A publically accessible web interface is also presented, which combines the thresholdable statistics of BEATS with queryable metadata terms, fostering potential avenues of research and facilitating the creation of highly personalized music playlists for clinical or recreational applications. PMID:25469636

Fingerprint separation: an application of ICA

NASA Astrophysics Data System (ADS)

Singh, Meenakshi; Singh, Deepak Kumar; Kalra, Prem Kumar

2008-04-01

Among all existing biometric techniques, fingerprint-based identification is the oldest method, which has been successfully used in numerous applications. Fingerprint-based identification is the most recognized tool in biometrics because of its reliability and accuracy. Fingerprint identification is done by matching questioned and known friction skin ridge impressions from fingers, palms, and toes to determine if the impressions are from the same finger (or palm, toe, etc.). There are many fingerprint matching algorithms which automate and facilitate the job of fingerprint matching, but for any of these algorithms matching can be difficult if the fingerprints are overlapped or mixed. In this paper, we have proposed a new algorithm for separating overlapped or mixed fingerprints so that the performance of the matching algorithms will improve when they are fed with these inputs. Independent Component Analysis (ICA) has been used as a tool to separate the overlapped or mixed fingerprints.

Incorporation of Fixed Installation Costs into Optimization of Groundwater Remediation with a New Efficient Surrogate Nonlinear Mixed Integer Optimization Algorithm

NASA Astrophysics Data System (ADS)

Shoemaker, Christine; Wan, Ying

2016-04-01

Optimization of nonlinear water resources management issues which have a mixture of fixed (e.g. construction cost for a well) and variable (e.g. cost per gallon of water pumped) costs has been not well addressed because prior algorithms for the resulting nonlinear mixed integer problems have required many groundwater simulations (with different configurations of decision variable), especially when the solution space is multimodal. In particular heuristic methods like genetic algorithms have often been used in the water resources area, but they require so many groundwater simulations that only small systems have been solved. Hence there is a need to have a method that reduces the number of expensive groundwater simulations. A recently published algorithm for nonlinear mixed integer programming using surrogates was shown in this study to greatly reduce the computational effort for obtaining accurate answers to problems involving fixed costs for well construction as well as variable costs for pumping because of a substantial reduction in the number of groundwater simulations required to obtain an accurate answer. Results are presented for a US EPA hazardous waste site. The nonlinear mixed integer surrogate algorithm is general and can be used on other problems arising in hydrology with open source codes in Matlab and python ("pySOT" in Bitbucket).

Video-rate nanoscopy enabled by sCMOS camera-specific single-molecule localization algorithms

PubMed Central

Huang, Fang; Hartwich, Tobias M. P.; Rivera-Molina, Felix E.; Lin, Yu; Duim, Whitney C.; Long, Jane J.; Uchil, Pradeep D.; Myers, Jordan R.; Baird, Michelle A.; Mothes, Walther; Davidson, Michael W.; Toomre, Derek; Bewersdorf, Joerg

2013-01-01

Newly developed scientific complementary metal–oxide–semiconductor (sCMOS) cameras have the potential to dramatically accelerate data acquisition in single-molecule switching nanoscopy (SMSN) while simultaneously increasing the effective quantum efficiency. However, sCMOS-intrinsic pixel-dependent readout noise substantially reduces the localization precision and introduces localization artifacts. Here we present algorithms that overcome these limitations and provide unbiased, precise localization of single molecules at the theoretical limit. In combination with a multi-emitter fitting algorithm, we demonstrate single-molecule localization super-resolution imaging at up to 32 reconstructed images/second (recorded at 1,600–3,200 camera frames/second) in both fixed and living cells. PMID:23708387

Numerical Roll Reversal Predictor Corrector Aerocapture and Precision Landing Guidance Algorithms for the Mars Surveyor Program 2001 Missions

NASA Technical Reports Server (NTRS)

Powell, Richard W.

1998-01-01

This paper describes the development and evaluation of a numerical roll reversal predictor-corrector guidance algorithm for the atmospheric flight portion of the Mars Surveyor Program 2001 Orbiter and Lander missions. The Lander mission utilizes direct entry and has a demanding requirement to deploy its parachute within 10 km of the target deployment point. The Orbiter mission utilizes aerocapture to achieve a precise captured orbit with a single atmospheric pass. Detailed descriptions of these predictor-corrector algorithms are given. Also, results of three and six degree-of-freedom Monte Carlo simulations which include navigation, aerodynamics, mass properties and atmospheric density uncertainties are presented.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Seventh Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2015-01-01

This paper presents an overview of the seventh revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This paper supersedes the previous documentation and presents a modification to the algorithm referred to as the Airborne Spacing for Terminal Arrival Routes version 13 (ASTAR13). This airborne self-spacing concept contains both trajectory-based and state-based mechanisms for calculating the speeds required to achieve or maintain a precise spacing interval. The trajectory-based capability allows for spacing operations prior to the aircraft being on a common path. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm adds the state-based capability in support of evolving industry standards relating to airborne self-spacing.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Eighth Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.; Swieringa, Kurt S.

2017-01-01

This paper presents an overview of the eighth revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This paper supersedes the previous documentation and presents a modification to the algorithm referred to as the Airborne Spacing for Terminal Arrival Routes version 13 (ASTAR13). This airborne self-spacing concept contains both trajectory-based and state-based mechanisms for calculating the speeds required to achieve or maintain a precise spacing interval with another aircraft. The trajectory-based capability allows for spacing operations prior to the aircraft being on a common path. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm supports the evolving industry standards relating to airborne self-spacing.

Simultaneous Mass Determination for Gravitationally Coupled Asteroids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baer, James; Chesley, Steven R., E-mail: jimbaer1@earthlink.net

The conventional least-squares asteroid mass determination algorithm allows us to solve for the mass of a large subject asteroid that is perturbing the trajectory of a smaller test asteroid. However, this algorithm is necessarily a first approximation, ignoring the possibility that the subject asteroid may itself be perturbed by the test asteroid, or that the encounter’s precise geometry may be entangled with encounters involving other asteroids. After reviewing the conventional algorithm, we use it to calculate the masses of 30 main-belt asteroids. Compared to our previous results, we find new mass estimates for eight asteroids (11 Parthenope, 27 Euterpe, 51more » Neimausa, 76 Freia, 121 Hermione, 324 Bamberga, 476 Hedwig, and 532 Herculina) and significantly more precise estimates for six others (2 Pallas, 3 Juno, 4 Vesta, 9 Metis, 16 Psyche, and 88 Thisbe). However, we also find that the conventional algorithm yields questionable results in several gravitationally coupled cases. To address such cases, we describe a new algorithm that allows the epoch state vectors of the subject asteroids to be included as solve-for parameters, allowing for the simultaneous solution of the masses and epoch state vectors of multiple subject and test asteroids. We then apply this algorithm to the same 30 main-belt asteroids and conclude that mass determinations resulting from current and future high-precision astrometric sources (such as Gaia ) should conduct a thorough search for possible gravitational couplings and account for their effects.« less

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

PubMed

Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

2013-08-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

PubMed Central

Kim, Yoonsang; Emery, Sherry

2013-01-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

High-precision relative position and attitude measurement for on-orbit maintenance of spacecraft

NASA Astrophysics Data System (ADS)

Zhu, Bing; Chen, Feng; Li, Dongdong; Wang, Ying

2018-02-01

In order to realize long-term on-orbit running of satellites, space stations, etc spacecrafts, in addition to the long life design of devices, The life of the spacecraft can also be extended by the on-orbit servicing and maintenance. Therefore, it is necessary to keep precise and detailed maintenance of key components. In this paper, a high-precision relative position and attitude measurement method used in the maintenance of key components is given. This method mainly considers the design of the passive cooperative marker, light-emitting device and high resolution camera in the presence of spatial stray light and noise. By using a series of algorithms, such as background elimination, feature extraction, position and attitude calculation, and so on, the high precision relative pose parameters as the input to the control system between key operation parts and maintenance equipment are obtained. The simulation results show that the algorithm is accurate and effective, satisfying the requirements of the precision operation technique.

Network-based machine learning and graph theory algorithms for precision oncology.

PubMed

Zhang, Wei; Chien, Jeremy; Yong, Jeongsik; Kuang, Rui

2017-01-01

Network-based analytics plays an increasingly important role in precision oncology. Growing evidence in recent studies suggests that cancer can be better understood through mutated or dysregulated pathways or networks rather than individual mutations and that the efficacy of repositioned drugs can be inferred from disease modules in molecular networks. This article reviews network-based machine learning and graph theory algorithms for integrative analysis of personal genomic data and biomedical knowledge bases to identify tumor-specific molecular mechanisms, candidate targets and repositioned drugs for personalized treatment. The review focuses on the algorithmic design and mathematical formulation of these methods to facilitate applications and implementations of network-based analysis in the practice of precision oncology. We review the methods applied in three scenarios to integrate genomic data and network models in different analysis pipelines, and we examine three categories of network-based approaches for repositioning drugs in drug-disease-gene networks. In addition, we perform a comprehensive subnetwork/pathway analysis of mutations in 31 cancer genome projects in the Cancer Genome Atlas and present a detailed case study on ovarian cancer. Finally, we discuss interesting observations, potential pitfalls and future directions in network-based precision oncology.

A hybrid Jaya algorithm for reliability-redundancy allocation problems

NASA Astrophysics Data System (ADS)

Ghavidel, Sahand; Azizivahed, Ali; Li, Li

2018-04-01

This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching-learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability-redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series-parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30-100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

Obtaining lower bounds from the progressive hedging algorithm for stochastic mixed-integer programs

DOE PAGES

Gade, Dinakar; Hackebeil, Gabriel; Ryan, Sarah M.; ...

2016-04-02

We present a method for computing lower bounds in the progressive hedging algorithm (PHA) for two-stage and multi-stage stochastic mixed-integer programs. Computing lower bounds in the PHA allows one to assess the quality of the solutions generated by the algorithm contemporaneously. The lower bounds can be computed in any iteration of the algorithm by using dual prices that are calculated during execution of the standard PHA. In conclusion, we report computational results on stochastic unit commitment and stochastic server location problem instances, and explore the relationship between key PHA parameters and the quality of the resulting lower bounds.

Micropower Mixed-signal VLSI Independent Component Analysis for Gradient Flow Acoustic Source Separation.

PubMed

Stanaćević, Milutin; Li, Shuo; Cauwenberghs, Gert

2016-07-01

A parallel micro-power mixed-signal VLSI implementation of independent component analysis (ICA) with reconfigurable outer-product learning rules is presented. With the gradient sensing of the acoustic field over a miniature microphone array as a pre-processing method, the proposed ICA implementation can separate and localize up to 3 sources in mild reverberant environment. The ICA processor is implemented in 0.5 µm CMOS technology and occupies 3 mm × 3 mm area. At 16 kHz sampling rate, ASIC consumes 195 µW power from a 3 V supply. The outer-product implementation of natural gradient and Herault-Jutten ICA update rules demonstrates comparable performance to benchmark FastICA algorithm in ideal conditions and more robust performance in noisy and reverberant environment. Experiments demonstrate perceptually clear separation and precise localization over wide range of separation angles of two speech sources presented through speakers positioned at 1.5 m from the array on a conference room table. The presented ASIC leads to a extreme small form factor and low power consumption microsystem for source separation and localization required in applications like intelligent hearing aids and wireless distributed acoustic sensor arrays.

Accurate Singular Values and Differential QD Algorithms

DTIC Science & Technology

1992-07-01

of the Cholesky Algorithm 5 4 The Quotient Difference Algorithm 8 5 Incorporation of Shifts 11 5.1 Shifted qd Algorithms...Effects of Finite Precision 18 7.1 Error Analysis - Overview ........ ........................... 18 7.2 High Relative Accuracy in the Presence of...showing that it was preferable to replace the DK zero-shift QR transform by two steps of zero-shift LR implemented in a qd (quotient- difference ) format

Bit Grooming: statistically accurate precision-preserving quantization with compression, evaluated in the netCDF Operators (NCO, v4.4.8+)

NASA Astrophysics Data System (ADS)

Zender, Charles S.

2016-09-01

Geoscientific models and measurements generate false precision (scientifically meaningless data bits) that wastes storage space. False precision can mislead (by implying noise is signal) and be scientifically pointless, especially for measurements. By contrast, lossy compression can be both economical (save space) and heuristic (clarify data limitations) without compromising the scientific integrity of data. Data quantization can thus be appropriate regardless of whether space limitations are a concern. We introduce, implement, and characterize a new lossy compression scheme suitable for IEEE floating-point data. Our new Bit Grooming algorithm alternately shaves (to zero) and sets (to one) the least significant bits of consecutive values to preserve a desired precision. This is a symmetric, two-sided variant of an algorithm sometimes called Bit Shaving that quantizes values solely by zeroing bits. Our variation eliminates the artificial low bias produced by always zeroing bits, and makes Bit Grooming more suitable for arrays and multi-dimensional fields whose mean statistics are important. Bit Grooming relies on standard lossless compression to achieve the actual reduction in storage space, so we tested Bit Grooming by applying the DEFLATE compression algorithm to bit-groomed and full-precision climate data stored in netCDF3, netCDF4, HDF4, and HDF5 formats. Bit Grooming reduces the storage space required by initially uncompressed and compressed climate data by 25-80 and 5-65 %, respectively, for single-precision values (the most common case for climate data) quantized to retain 1-5 decimal digits of precision. The potential reduction is greater for double-precision datasets. When used aggressively (i.e., preserving only 1-2 digits), Bit Grooming produces storage reductions comparable to other quantization techniques such as Linear Packing. Unlike Linear Packing, whose guaranteed precision rapidly degrades within the relatively narrow dynamic range of values that it can compress, Bit Grooming guarantees the specified precision throughout the full floating-point range. Data quantization by Bit Grooming is irreversible (i.e., lossy) yet transparent, meaning that no extra processing is required by data users/readers. Hence Bit Grooming can easily reduce data storage volume without sacrificing scientific precision or imposing extra burdens on users.

Precise Aperture-Dependent Motion Compensation with Frequency Domain Fast Back-Projection Algorithm.

PubMed

Zhang, Man; Wang, Guanyong; Zhang, Lei

2017-10-26

Precise azimuth-variant motion compensation (MOCO) is an essential and difficult task for high-resolution synthetic aperture radar (SAR) imagery. In conventional post-filtering approaches, residual azimuth-variant motion errors are generally compensated through a set of spatial post-filters, where the coarse-focused image is segmented into overlapped blocks concerning the azimuth-dependent residual errors. However, image domain post-filtering approaches, such as precise topography- and aperture-dependent motion compensation algorithm (PTA), have difficulty of robustness in declining, when strong motion errors are involved in the coarse-focused image. In this case, in order to capture the complete motion blurring function within each image block, both the block size and the overlapped part need necessary extension leading to degeneration of efficiency and robustness inevitably. Herein, a frequency domain fast back-projection algorithm (FDFBPA) is introduced to deal with strong azimuth-variant motion errors. FDFBPA disposes of the azimuth-variant motion errors based on a precise azimuth spectrum expression in the azimuth wavenumber domain. First, a wavenumber domain sub-aperture processing strategy is introduced to accelerate computation. After that, the azimuth wavenumber spectrum is partitioned into a set of wavenumber blocks, and each block is formed into a sub-aperture coarse resolution image via the back-projection integral. Then, the sub-aperture images are straightforwardly fused together in azimuth wavenumber domain to obtain a full resolution image. Moreover, chirp-Z transform (CZT) is also introduced to implement the sub-aperture back-projection integral, increasing the efficiency of the algorithm. By disusing the image domain post-filtering strategy, robustness of the proposed algorithm is improved. Both simulation and real-measured data experiments demonstrate the effectiveness and superiority of the proposal.

Filtered-x generalized mixed norm (FXGMN) algorithm for active noise control

NASA Astrophysics Data System (ADS)

Song, Pucha; Zhao, Haiquan

2018-07-01

The standard adaptive filtering algorithm with a single error norm exhibits slow convergence rate and poor noise reduction performance under specific environments. To overcome this drawback, a filtered-x generalized mixed norm (FXGMN) algorithm for active noise control (ANC) system is proposed. The FXGMN algorithm is developed by using a convex mixture of lp and lq norms as the cost function that it can be viewed as a generalized version of the most existing adaptive filtering algorithms, and it will reduce to a specific algorithm by choosing certain parameters. Especially, it can be used to solve the ANC under Gaussian and non-Gaussian noise environments (including impulsive noise with symmetric α -stable (SαS) distribution). To further enhance the algorithm performance, namely convergence speed and noise reduction performance, a convex combination of the FXGMN algorithm (C-FXGMN) is presented. Moreover, the computational complexity of the proposed algorithms is analyzed, and a stability condition for the proposed algorithms is provided. Simulation results show that the proposed FXGMN and C-FXGMN algorithms can achieve better convergence speed and higher noise reduction as compared to other existing algorithms under various noise input conditions, and the C-FXGMN algorithm outperforms the FXGMN.

Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis

PubMed Central

Holloway, Andrew J; Oshlack, Alicia; Diyagama, Dileepa S; Bowtell, David DL; Smyth, Gordon K

2006-01-01

Background Concerns are often raised about the accuracy of microarray technologies and the degree of cross-platform agreement, but there are yet no methods which can unambiguously evaluate precision and sensitivity for these technologies on a whole-array basis. Results A methodology is described for evaluating the precision and sensitivity of whole-genome gene expression technologies such as microarrays. The method consists of an easy-to-construct titration series of RNA samples and an associated statistical analysis using non-linear regression. The method evaluates the precision and responsiveness of each microarray platform on a whole-array basis, i.e., using all the probes, without the need to match probes across platforms. An experiment is conducted to assess and compare four widely used microarray platforms. All four platforms are shown to have satisfactory precision but the commercial platforms are superior for resolving differential expression for genes at lower expression levels. The effective precision of the two-color platforms is improved by allowing for probe-specific dye-effects in the statistical model. The methodology is used to compare three data extraction algorithms for the Affymetrix platforms, demonstrating poor performance for the commonly used proprietary algorithm relative to the other algorithms. For probes which can be matched across platforms, the cross-platform variability is decomposed into within-platform and between-platform components, showing that platform disagreement is almost entirely systematic rather than due to measurement variability. Conclusion The results demonstrate good precision and sensitivity for all the platforms, but highlight the need for improved probe annotation. They quantify the extent to which cross-platform measures can be expected to be less accurate than within-platform comparisons for predicting disease progression or outcome. PMID:17118209

Low complexity 1D IDCT for 16-bit parallel architectures

NASA Astrophysics Data System (ADS)

Bivolarski, Lazar

2007-09-01

This paper shows that using the Loeffler, Ligtenberg, and Moschytz factorization of 8-point IDCT [2] one-dimensional (1-D) algorithm as a fast approximation of the Discrete Cosine Transform (DCT) and using only 16 bit numbers, it is possible to create in an IEEE 1180-1990 compliant and multiplierless algorithm with low computational complexity. This algorithm as characterized by its structure is efficiently implemented on parallel high performance architectures as well as due to its low complexity is sufficient for wide range of other architectures. Additional constraint on this work was the requirement of compliance with the existing MPEG standards. The hardware implementation complexity and low resources where also part of the design criteria for this algorithm. This implementation is also compliant with the precision requirements described in MPEG IDCT precision specification ISO/IEC 23002-1. Complexity analysis is performed as an extension to the simple measure of shifts and adds for the multiplierless algorithm as additional operations are included in the complexity measure to better describe the actual transform implementation complexity.

Research on registration algorithm for check seal verification

NASA Astrophysics Data System (ADS)

Wang, Shuang; Liu, Tiegen

2008-03-01

Nowadays seals play an important role in China. With the development of social economy, the traditional method of manual check seal identification can't meet the need s of banking transactions badly. This paper focus on pre-processing and registration algorithm for check seal verification using theory of image processing and pattern recognition. First of all, analyze the complex characteristics of check seals. To eliminate the difference of producing conditions and the disturbance caused by background and writing in check image, many methods are used in the pre-processing of check seal verification, such as color components transformation, linearity transform to gray-scale image, medium value filter, Otsu, close calculations and labeling algorithm of mathematical morphology. After the processes above, the good binary seal image can be obtained. On the basis of traditional registration algorithm, a double-level registration method including rough and precise registration method is proposed. The deflection angle of precise registration method can be precise to 0.1°. This paper introduces the concepts of difference inside and difference outside and use the percent of difference inside and difference outside to judge whether the seal is real or fake. The experimental results of a mass of check seals are satisfied. It shows that the methods and algorithmic presented have good robustness to noise sealing conditions and satisfactory tolerance of difference within class.

Assessment of Mixed-Layer Height Estimation from Single-wavelength Ceilometer Profiles.

PubMed

Knepp, Travis N; Szykman, James J; Long, Russell; Duvall, Rachelle M; Krug, Jonathan; Beaver, Melinda; Cavender, Kevin; Kronmiller, Keith; Wheeler, Michael; Delgado, Ruben; Hoff, Raymond; Berkoff, Timothy; Olson, Erik; Clark, Richard; Wolfe, Daniel; Van Gilst, David; Neil, Doreen

2017-01-01

Differing boundary/mixed-layer height measurement methods were assessed in moderately-polluted and clean environments, with a focus on the Vaisala CL51 ceilometer. This intercomparison was performed as part of ongoing measurements at the Chemistry And Physics of the Atmospheric Boundary Layer Experiment (CAPABLE) site in Hampton, Virginia and during the 2014 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign that took place in and around Denver, Colorado. We analyzed CL51 data that were collected via two different methods (BLView software, which applied correction factors, and simple terminal emulation logging) to determine the impact of data collection methodology. Further, we evaluated the STRucture of the ATmosphere (STRAT) algorithm as an open-source alternative to BLView (note that the current work presents an evaluation of the BLView and STRAT algorithms and does not intend to act as a validation of either). Filtering criteria were defined according to the change in mixed-layer height (MLH) distributions for each instrument and algorithm and were applied throughout the analysis to remove high-frequency fluctuations from the MLH retrievals. Of primary interest was determining how the different data-collection methodologies and algorithms compare to each other and to radiosonde-derived boundary-layer heights when deployed as part of a larger instrument network. We determined that data-collection methodology is not as important as the processing algorithm and that much of the algorithm differences might be driven by impacts of local meteorology and precipitation events that pose algorithm difficulties. The results of this study show that a common processing algorithm is necessary for LIght Detection And Ranging (LIDAR)-based MLH intercomparisons, and ceilometer-network operation and that sonde-derived boundary layer heights are higher (10-15% at mid-day) than LIDAR-derived mixed-layer heights. We show that averaging the retrieved MLH to 1-hour resolution (an appropriate time scale for a priori data model initialization) significantly improved correlation between differing instruments and differing algorithms.

Automatic arrival time detection for earthquakes based on Modified Laplacian of Gaussian filter

NASA Astrophysics Data System (ADS)

Saad, Omar M.; Shalaby, Ahmed; Samy, Lotfy; Sayed, Mohammed S.

2018-04-01

Precise identification of onset time for an earthquake is imperative in the right figuring of earthquake's location and different parameters that are utilized for building seismic catalogues. P-wave arrival detection of weak events or micro-earthquakes cannot be precisely determined due to background noise. In this paper, we propose a novel approach based on Modified Laplacian of Gaussian (MLoG) filter to detect the onset time even in the presence of very weak signal-to-noise ratios (SNRs). The proposed algorithm utilizes a denoising-filter algorithm to smooth the background noise. In the proposed algorithm, we employ the MLoG mask to filter the seismic data. Afterward, we apply a Dual-threshold comparator to detect the onset time of the event. The results show that the proposed algorithm can detect the onset time for micro-earthquakes accurately, with SNR of -12 dB. The proposed algorithm achieves an onset time picking accuracy of 93% with a standard deviation error of 0.10 s for 407 field seismic waveforms. Also, we compare the results with short and long time average algorithm (STA/LTA) and the Akaike Information Criterion (AIC), and the proposed algorithm outperforms them.

The research of automatic speed control algorithm based on Green CBTC

NASA Astrophysics Data System (ADS)

Lin, Ying; Xiong, Hui; Wang, Xiaoliang; Wu, Youyou; Zhang, Chuanqi

2017-06-01

Automatic speed control algorithm is one of the core technologies of train operation control system. It’s a typical multi-objective optimization control algorithm, which achieve the train speed control for timing, comfort, energy-saving and precise parking. At present, the train speed automatic control technology is widely used in metro and inter-city railways. It has been found that the automatic speed control technology can effectively reduce the driver’s intensity, and improve the operation quality. However, the current used algorithm is poor at energy-saving, even not as good as manual driving. In order to solve the problem of energy-saving, this paper proposes an automatic speed control algorithm based on Green CBTC system. Based on the Green CBTC system, the algorithm can adjust the operation status of the train to improve the efficient using rate of regenerative braking feedback energy while ensuring the timing, comfort and precise parking targets. Due to the reason, the energy-using of Green CBTC system is lower than traditional CBTC system. The simulation results show that the algorithm based on Green CBTC system can effectively reduce the energy-using due to the improvement of the using rate of regenerative braking feedback energy.

PPP Sliding Window Algorithm and Its Application in Deformation Monitoring.

PubMed

Song, Weiwei; Zhang, Rui; Yao, Yibin; Liu, Yanyan; Hu, Yuming

2016-05-31

Compared with the double-difference relative positioning method, the precise point positioning (PPP) algorithm can avoid the selection of a static reference station and directly measure the three-dimensional position changes at the observation site and exhibit superiority in a variety of deformation monitoring applications. However, because of the influence of various observing errors, the accuracy of PPP is generally at the cm-dm level, which cannot meet the requirements needed for high precision deformation monitoring. For most of the monitoring applications, the observation stations maintain stationary, which can be provided as a priori constraint information. In this paper, a new PPP algorithm based on a sliding window was proposed to improve the positioning accuracy. Firstly, data from IGS tracking station was processed using both traditional and new PPP algorithm; the results showed that the new algorithm can effectively improve positioning accuracy, especially for the elevation direction. Then, an earthquake simulation platform was used to simulate an earthquake event; the results illustrated that the new algorithm can effectively detect the vibrations change of a reference station during an earthquake. At last, the observed Wenchuan earthquake experimental results showed that the new algorithm was feasible to monitor the real earthquakes and provide early-warning alerts.

Dynamic metrology and data processing for precision freeform optics fabrication and testing

NASA Astrophysics Data System (ADS)

Aftab, Maham; Trumper, Isaac; Huang, Lei; Choi, Heejoo; Zhao, Wenchuan; Graves, Logan; Oh, Chang Jin; Kim, Dae Wook

2017-06-01

Dynamic metrology holds the key to overcoming several challenging limitations of conventional optical metrology, especially with regards to precision freeform optical elements. We present two dynamic metrology systems: 1) adaptive interferometric null testing; and 2) instantaneous phase shifting deflectometry, along with an overview of a gradient data processing and surface reconstruction technique. The adaptive null testing method, utilizing a deformable mirror, adopts a stochastic parallel gradient descent search algorithm in order to dynamically create a null testing condition for unknown freeform optics. The single-shot deflectometry system implemented on an iPhone uses a multiplexed display pattern to enable dynamic measurements of time-varying optical components or optics in vibration. Experimental data, measurement accuracy / precision, and data processing algorithms are discussed.

Precise Image-Based Motion Estimation for Autonomous Small Body Exploration

NASA Technical Reports Server (NTRS)

Johnson, Andrew E.; Matthies, Larry H.

1998-01-01

Space science and solar system exploration are driving NASA to develop an array of small body missions ranging in scope from near body flybys to complete sample return. This paper presents an algorithm for onboard motion estimation that will enable the precision guidance necessary for autonomous small body landing. Our techniques are based on automatic feature tracking between a pair of descent camera images followed by two frame motion estimation and scale recovery using laser altimetry data. The output of our algorithm is an estimate of rigid motion (attitude and position) and motion covariance between frames. This motion estimate can be passed directly to the spacecraft guidance and control system to enable rapid execution of safe and precise trajectories.

A refined methodology for modeling volume quantification performance in CT

NASA Astrophysics Data System (ADS)

Chen, Baiyu; Wilson, Joshua; Samei, Ehsan

2014-03-01

The utility of CT lung nodule volume quantification technique depends on the precision of the quantification. To enable the evaluation of quantification precision, we previously developed a mathematical model that related precision to image resolution and noise properties in uniform backgrounds in terms of an estimability index (e'). The e' was shown to predict empirical precision across 54 imaging and reconstruction protocols, but with different correlation qualities for FBP and iterative reconstruction (IR) due to the non-linearity of IR impacted by anatomical structure. To better account for the non-linearity of IR, this study aimed to refine the noise characterization of the model in the presence of textured backgrounds. Repeated scans of an anthropomorphic lung phantom were acquired. Subtracted images were used to measure the image quantum noise, which was then used to adjust the noise component of the e' calculation measured from a uniform region. In addition to the model refinement, the validation of the model was further extended to 2 nodule sizes (5 and 10 mm) and 2 segmentation algorithms. Results showed that the magnitude of IR's quantum noise was significantly higher in structured backgrounds than in uniform backgrounds (ASiR, 30-50%; MBIR, 100-200%). With the refined model, the correlation between e' values and empirical precision no longer depended on reconstruction algorithm. In conclusion, the model with refined noise characterization relfected the nonlinearity of iterative reconstruction in structured background, and further showed successful prediction of quantification precision across a variety of nodule sizes, dose levels, slice thickness, reconstruction algorithms, and segmentation software.

An Evaluation of a Flight Deck Interval Management Algorithm Including Delayed Target Trajectories

NASA Technical Reports Server (NTRS)

Swieringa, Kurt A.; Underwood, Matthew C.; Barmore, Bryan; Leonard, Robert D.

2014-01-01

NASA's first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature air traffic management technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise timebased scheduling in the terminal airspace; Controller Managed Spacing (CMS), which provides controllers with decision support tools enabling precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain precise in-trail spacing. During high demand operations, TMA-TM may produce a schedule and corresponding aircraft trajectories that include delay to ensure that a particular aircraft will be properly spaced from other aircraft at each schedule waypoint. These delayed trajectories are not communicated to the automation onboard the aircraft, forcing the IM aircraft to use the published speeds to estimate the target aircraft's estimated time of arrival. As a result, the aircraft performing IM operations may follow an aircraft whose TMA-TM generated trajectories have substantial speed deviations from the speeds expected by the spacing algorithm. Previous spacing algorithms were not designed to handle this magnitude of uncertainty. A simulation was conducted to examine a modified spacing algorithm with the ability to follow aircraft flying delayed trajectories. The simulation investigated the use of the new spacing algorithm with various delayed speed profiles and wind conditions, as well as several other variables designed to simulate real-life variability. The results and conclusions of this study indicate that the new spacing algorithm generally exhibits good performance; however, some types of target aircraft speed profiles can cause the spacing algorithm to command less than optimal speed control behavior.

Latest results from Daya Bay

NASA Astrophysics Data System (ADS)

Vorobel, Vit; Daya Bay Collaboration

2017-07-01

The Daya Bay Reactor Neutrino Experiment was designed to measure θ 13, the smallest mixing angle in the three-neutrino mixing framework, with unprecedented precision. The experiment consists of eight functionally identical detectors placed underground at different baselines from three pairs of nuclear reactors in South China. Since Dec. 2011, the experiment has been running stably for more than 4 years, and has collected the largest reactor anti-neutrino sample to date. Daya Bay is able to greatly improve the precision on θ 13 and to make an independent measurement of the effective mass splitting in the electron antineutrino disappearance channel. Daya Bay can also perform a number of other precise measurements, such as a high-statistics determination of the absolute reactor antineutrino flux and spectrum, as well as a search for sterile neutrino mixing, among others. The most recent results from Daya Bay are discussed in this paper, as well as the current status and future prospects of the experiment.

Case-Mix for Performance Management: A Risk Algorithm Based on ICD-10-CM.

PubMed

Gao, Jian; Moran, Eileen; Almenoff, Peter L

2018-06-01

Accurate risk adjustment is the key to a reliable comparison of cost and quality performance among providers and hospitals. However, the existing case-mix algorithms based on age, sex, and diagnoses can only explain up to 50% of the cost variation. More accurate risk adjustment is desired for provider performance assessment and improvement. To develop a case-mix algorithm that hospitals and payers can use to measure and compare cost and quality performance of their providers. All 6,048,895 patients with valid diagnoses and cost recorded in the US Veterans health care system in fiscal year 2016 were included in this study. The dependent variable was total cost at the patient level, and the explanatory variables were age, sex, and comorbidities represented by 762 clinically homogeneous groups, which were created by expanding the 283 categories from Clinical Classifications Software based on ICD-10-CM codes. The split-sample method was used to assess model overfitting and coefficient stability. The predictive power of the algorithms was ascertained by comparing the R, mean absolute percentage error, root mean square error, predictive ratios, and c-statistics. The expansion of the Clinical Classifications Software categories resulted in higher predictive power. The R reached 0.72 and 0.52 for the transformed and raw scale cost, respectively. The case-mix algorithm we developed based on age, sex, and diagnoses outperformed the existing case-mix models reported in the literature. The method developed in this study can be used by other health systems to produce tailored risk models for their specific purpose.

Treatment Algorithms Based on Tumor Molecular Profiling: The Essence of Precision Medicine Trials.

PubMed

Le Tourneau, Christophe; Kamal, Maud; Tsimberidou, Apostolia-Maria; Bedard, Philippe; Pierron, Gaëlle; Callens, Céline; Rouleau, Etienne; Vincent-Salomon, Anne; Servant, Nicolas; Alt, Marie; Rouzier, Roman; Paoletti, Xavier; Delattre, Olivier; Bièche, Ivan

2016-04-01

With the advent of high-throughput molecular technologies, several precision medicine (PM) studies are currently ongoing that include molecular screening programs and PM clinical trials. Molecular profiling programs establish the molecular profile of patients' tumors with the aim to guide therapy based on identified molecular alterations. The aim of prospective PM clinical trials is to assess the clinical utility of tumor molecular profiling and to determine whether treatment selection based on molecular alterations produces superior outcomes compared with unselected treatment. These trials use treatment algorithms to assign patients to specific targeted therapies based on tumor molecular alterations. These algorithms should be governed by fixed rules to ensure standardization and reproducibility. Here, we summarize key molecular, biological, and technical criteria that, in our view, should be addressed when establishing treatment algorithms based on tumor molecular profiling for PM trials. © The Author 2015. Published by Oxford University Press.

Predicting surface fuel models and fuel metrics using lidar and CIR imagery in a dense mixed conifer forest

Treesearch

Marek K. Jakubowksi; Qinghua Guo; Brandon Collins; Scott Stephens; Maggi Kelly

2013-01-01

We compared the ability of several classification and regression algorithms to predict forest stand structure metrics and standard surface fuel models. Our study area spans a dense, topographically complex Sierra Nevada mixed-conifer forest. We used clustering, regression trees, and support vector machine algorithms to analyze high density (average 9 pulses/m

Multi-Target Tracking via Mixed Integer Optimization

DTIC Science & Technology

2016-05-13

solving these two problems separately, however few algorithms attempt to solve these simultaneously and even fewer utilize optimization. In this paper we...introduce a new mixed integer optimization (MIO) model which solves the data association and trajectory estimation problems simultaneously by minimizing...Kalman filter [5], which updates the trajectory estimates before the algorithm progresses forward to the next scan. This process repeats sequentially

Unsupervised categorization method of graphemes on handwritten manuscripts: application to style recognition

NASA Astrophysics Data System (ADS)

Daher, H.; Gaceb, D.; Eglin, V.; Bres, S.; Vincent, N.

2012-01-01

We present in this paper a feature selection and weighting method for medieval handwriting images that relies on codebooks of shapes of small strokes of characters (graphemes that are issued from the decomposition of manuscripts). These codebooks are important to simplify the automation of the analysis, the manuscripts transcription and the recognition of styles or writers. Our approach provides a precise features weighting by genetic algorithms and a highperformance methodology for the categorization of the shapes of graphemes by using graph coloring into codebooks which are applied in turn on CBIR (Content Based Image Retrieval) in a mixed handwriting database containing different pages from different writers, periods of the history and quality. We show how the coupling of these two mechanisms 'features weighting - graphemes classification' can offer a better separation of the forms to be categorized by exploiting their grapho-morphological, their density and their significant orientations particularities.

Markov chain sampling of the O(n) loop models on the infinite plane

NASA Astrophysics Data System (ADS)

Herdeiro, Victor

2017-07-01

A numerical method was recently proposed in Herdeiro and Doyon [Phys. Rev. E 94, 043322 (2016), 10.1103/PhysRevE.94.043322] showing a precise sampling of the infinite plane two-dimensional critical Ising model for finite lattice subsections. The present note extends the method to a larger class of models, namely the O(n) loop gas models for n ∈(1 ,2 ] . We argue that even though the Gibbs measure is nonlocal, it is factorizable on finite subsections when sufficient information on the loops touching the boundaries is stored. Our results attempt to show that provided an efficient Markov chain mixing algorithm and an improved discrete lattice dilation procedure the planar limit of the O(n) models can be numerically studied with efficiency similar to the Ising case. This confirms that scale invariance is the only requirement for the present numerical method to work.

Intrinsic fluorescence spectra characteristics of vitamin B1, B2, and B6

NASA Astrophysics Data System (ADS)

Yang, Hui; Xiao, Xue; Zhao, Xuesong; Hu, Lan; Lv, Caofang; Yin, Zhangkun

2015-11-01

This paper presents the intrinsic fluorescence characteristics of vitamin B1, B2 and B6 measured with 3D fluorescence Spectrophotometer. Three strong fluorescence areas of vitamin B2 locate at λex/λem=270/525nm, 370/525nm and 450/525nm, one fluorescence areas of vitamin B1 locates at λex/λem=370/460nm, two fluorescence areas of vitamin B6 locates at λex/λem=250/370nm and 325/370nm were found. The influence of pH of solution to the fluorescence profile was also discussed. Using the PARAFAC algorithm, 10 vitamin B1, B2 and B6 mixed solutions were successfully decomposed, and the emission profiles, excitation profiles, central wavelengths and the concentration of the three components were retrieved precisely through about 5 iteration times.

A novel approach for individual tree crown delineation using lidar data

NASA Astrophysics Data System (ADS)

Liu, Tao

Individual tree crown delineation (ITCD) is an important technique to support precision forestry. ITCD is particularly difficult for deciduous forests where the existence of multiple branches can lead to false tree top detection. This thesis focused on developing a new ITCD model, which consists of two components: (1) boundary refinement using a novel algorithm called Fishing Net Dragging (FiND), and (2) segment merging using boundary classification. The proposed ITCD model was tested in both deciduous and mixed forests, attaining an overall accuracy of 74% and 78%, respectively. This compared favorably to an ITCD method commonly cited in the literature, which attained 41% and 51% on the same plots. To facilitate comparison of research in the ITCD community, this thesis also developed a new accuracy assessment scheme for ITCD. This new accuracy assessment is easy to interpret and convenient to implement while comprehensively evaluating ITCD accuracy.

Evaluation of orbits with incomplete knowledge of the mathematical expectancy and the matrix of covariation of errors

NASA Technical Reports Server (NTRS)

Bakhshiyan, B. T.; Nazirov, R. R.; Elyasberg, P. E.

1980-01-01

The problem of selecting the optimal algorithm of filtration and the optimal composition of the measurements is examined assuming that the precise values of the mathematical expectancy and the matrix of covariation of errors are unknown. It is demonstrated that the optimal algorithm of filtration may be utilized for making some parameters more precise (for example, the parameters of the gravitational fields) after preliminary determination of the elements of the orbit by a simpler method of processing (for example, the method of least squares).

Algorithm Diversity for Resilent Systems

DTIC Science & Technology

2016-06-27

data structures. 15. SUBJECT TERMS computer security, software diversity, program transformation 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF 18...systematic method for transforming Datalog rules with general universal and existential quantification into efficient algorithms with precise complexity...worst case in the size of the ground rules. There are numerous choices during the transformation that lead to diverse algorithms and different

Classification of LIDAR Data for Generating a High-Precision Roadway Map

NASA Astrophysics Data System (ADS)

Jeong, J.; Lee, I.

2016-06-01

Generating of a highly precise map grows up with development of autonomous driving vehicles. The highly precise map includes a precision of centimetres level unlike an existing commercial map with the precision of meters level. It is important to understand road environments and make a decision for autonomous driving since a robust localization is one of the critical challenges for the autonomous driving car. The one of source data is from a Lidar because it provides highly dense point cloud data with three dimensional position, intensities and ranges from the sensor to target. In this paper, we focus on how to segment point cloud data from a Lidar on a vehicle and classify objects on the road for the highly precise map. In particular, we propose the combination with a feature descriptor and a classification algorithm in machine learning. Objects can be distinguish by geometrical features based on a surface normal of each point. To achieve correct classification using limited point cloud data sets, a Support Vector Machine algorithm in machine learning are used. Final step is to evaluate accuracies of obtained results by comparing them to reference data The results show sufficient accuracy and it will be utilized to generate a highly precise road map.

High-precision measurements of cementless acetabular components using model-based RSA: an experimental study.

PubMed

Baad-Hansen, Thomas; Kold, Søren; Kaptein, Bart L; Søballe, Kjeld

2007-08-01

In RSA, tantalum markers attached to metal-backed acetabular cups are often difficult to detect on stereo radiographs due to the high density of the metal shell. This results in occlusion of the prosthesis markers and may lead to inconclusive migration results. Within the last few years, new software systems have been developed to solve this problem. We compared the precision of 3 RSA systems in migration analysis of the acetabular component. A hemispherical and a non-hemispherical acetabular component were mounted in a phantom. Both acetabular components underwent migration analyses with 3 different RSA systems: conventional RSA using tantalum markers, an RSA system using a hemispherical cup algorithm, and a novel model-based RSA system. We found narrow confidence intervals, indicating high precision of the conventional marker system and model-based RSA with regard to migration and rotation. The confidence intervals of conventional RSA and model-based RSA were narrower than those of the hemispherical cup algorithm-based system regarding cup migration and rotation. The model-based RSA software combines the precision of the conventional RSA software with the convenience of the hemispherical cup algorithm-based system. Based on our findings, we believe that these new tools offer an improvement in the measurement of acetabular component migration.

Partial discharge localization in power transformers based on the sequential quadratic programming-genetic algorithm adopting acoustic emission techniques

NASA Astrophysics Data System (ADS)

Liu, Hua-Long; Liu, Hua-Dong

2014-10-01

Partial discharge (PD) in power transformers is one of the prime reasons resulting in insulation degradation and power faults. Hence, it is of great importance to study the techniques of the detection and localization of PD in theory and practice. The detection and localization of PD employing acoustic emission (AE) techniques, as a kind of non-destructive testing, plus due to the advantages of powerful capability of locating and high precision, have been paid more and more attention. The localization algorithm is the key factor to decide the localization accuracy in AE localization of PD. Many kinds of localization algorithms exist for the PD source localization adopting AE techniques including intelligent and non-intelligent algorithms. However, the existed algorithms possess some defects such as the premature convergence phenomenon, poor local optimization ability and unsuitability for the field applications. To overcome the poor local optimization ability and easily caused premature convergence phenomenon of the fundamental genetic algorithm (GA), a new kind of improved GA is proposed, namely the sequence quadratic programming-genetic algorithm (SQP-GA). For the hybrid optimization algorithm, SQP-GA, the sequence quadratic programming (SQP) algorithm which is used as a basic operator is integrated into the fundamental GA, so the local searching ability of the fundamental GA is improved effectively and the premature convergence phenomenon is overcome. Experimental results of the numerical simulations of benchmark functions show that the hybrid optimization algorithm, SQP-GA, is better than the fundamental GA in the convergence speed and optimization precision, and the proposed algorithm in this paper has outstanding optimization effect. At the same time, the presented SQP-GA in the paper is applied to solve the ultrasonic localization problem of PD in transformers, then the ultrasonic localization method of PD in transformers based on the SQP-GA is proposed. And localization results based on the SQP-GA are compared with some algorithms such as the GA, some other intelligent and non-intelligent algorithms. The results of calculating examples both stimulated and spot experiments demonstrate that the localization method based on the SQP-GA can effectively prevent the results from getting trapped into the local optimum values, and the localization method is of great feasibility and very suitable for the field applications, and the precision of localization is enhanced, and the effectiveness of localization is ideal and satisfactory.

Understanding and Optimizing Asynchronous Low-Precision Stochastic Gradient Descent

PubMed Central

De Sa, Christopher; Feldman, Matthew; Ré, Christopher; Olukotun, Kunle

2018-01-01

Stochastic gradient descent (SGD) is one of the most popular numerical algorithms used in machine learning and other domains. Since this is likely to continue for the foreseeable future, it is important to study techniques that can make it run fast on parallel hardware. In this paper, we provide the first analysis of a technique called Buckwild! that uses both asynchronous execution and low-precision computation. We introduce the DMGC model, the first conceptualization of the parameter space that exists when implementing low-precision SGD, and show that it provides a way to both classify these algorithms and model their performance. We leverage this insight to propose and analyze techniques to improve the speed of low-precision SGD. First, we propose software optimizations that can increase throughput on existing CPUs by up to 11×. Second, we propose architectural changes, including a new cache technique we call an obstinate cache, that increase throughput beyond the limits of current-generation hardware. We also implement and analyze low-precision SGD on the FPGA, which is a promising alternative to the CPU for future SGD systems. PMID:29391770

A high precision position sensor design and its signal processing algorithm for a maglev train.

PubMed

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.

A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train

PubMed Central

Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen

2012-01-01

High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run. PMID:22778582

Identification of cultivated land using remote sensing images based on object-oriented artificial bee colony algorithm

NASA Astrophysics Data System (ADS)

Li, Nan; Zhu, Xiufang

2017-04-01

Cultivated land resources is the key to ensure food security. Timely and accurate access to cultivated land information is conducive to a scientific planning of food production and management policies. The GaoFen 1 (GF-1) images have high spatial resolution and abundant texture information and thus can be used to identify fragmentized cultivated land. In this paper, an object-oriented artificial bee colony algorithm was proposed for extracting cultivated land from GF-1 images. Firstly, the GF-1 image was segmented by eCognition software and some samples from the segments were manually identified into 2 types (cultivated land and non-cultivated land). Secondly, the artificial bee colony (ABC) algorithm was used to search for classification rules based on the spectral and texture information extracted from the image objects. Finally, the extracted classification rules were used to identify the cultivated land area on the image. The experiment was carried out in Hongze area, Jiangsu Province using wide field-of-view sensor on the GF-1 satellite image. The total precision of classification result was 94.95%, and the precision of cultivated land was 92.85%. The results show that the object-oriented ABC algorithm can overcome the defect of insufficient spectral information in GF-1 images and obtain high precision in cultivated identification.

Photovoltaic Cells Mppt Algorithm and Design of Controller Monitoring System

NASA Astrophysics Data System (ADS)

Meng, X. Z.; Feng, H. B.

2017-10-01

This paper combined the advantages of each maximum power point tracking (MPPT) algorithm, put forward a kind of algorithm with higher speed and higher precision, based on this algorithm designed a maximum power point tracking controller with ARM. The controller, communication technology and PC software formed a control system. Results of the simulation and experiment showed that the process of maximum power tracking was effective, and the system was stable.

Petro-elastic modelling and characterization of solid-filled reservoirs: Comparative analysis on a Triassic North Sea reservoir

NASA Astrophysics Data System (ADS)

Auduson, Aaron E.

2018-07-01

One of the most common problems in the North Sea is the occurrence of salt (solid) in the pores of Triassic sandstones. Many wells have failed due to interpretation errors based conventional substitution as described by the Gassmann equation. A way forward is to device a means to model and characterize the salt-plugging scenarios. Modelling the effects of fluid and solids on rock velocity and density will ascertain the influence of pore material types on seismic data. In this study, two different rock physics modelling approaches are adopted in solid-fluid substitution, namely the extended Gassmann theory and multi-mineral mixing modelling. Using the modified new Gassmann equation, solid-and-fluid substitutions were performed from gas or water filling in the hydrocarbon reservoirs to salt materials being the pore-filling. Inverse substitutions were also performed from salt-filled case to gas- and water-filled scenarios. The modelling results show very consistent results - Salt-plugged wells clearly showing different elastic parameters when compared with gas- and water-bearing wells. While the Gassmann equation-based modelling was used to discretely compute effective bulk and shear moduli of the salt plugs, the algorithm based on the mineral-mixing (Hashin-Shtrikman) can only predict elastic moduli in a narrow range. Thus, inasmuch as both of these methods can be used to model elastic parameters and characterize pore-fill scenarios, the New Gassmann-based algorithm, which is capable of precisely predicting the elastic parameters, is recommended for use in forward seismic modelling and characterization of this reservoir and other reservoir types. This will significantly help in reducing seismic interpretation errors.

Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.

PubMed

McParland, D; Phillips, C M; Brennan, L; Roche, H M; Gormley, I C

2017-12-10

The LIPGENE-SU.VI.MAX study, like many others, recorded high-dimensional continuous phenotypic data and categorical genotypic data. LIPGENE-SU.VI.MAX focuses on the need to account for both phenotypic and genetic factors when studying the metabolic syndrome (MetS), a complex disorder that can lead to higher risk of type 2 diabetes and cardiovascular disease. Interest lies in clustering the LIPGENE-SU.VI.MAX participants into homogeneous groups or sub-phenotypes, by jointly considering their phenotypic and genotypic data, and in determining which variables are discriminatory. A novel latent variable model that elegantly accommodates high dimensional, mixed data is developed to cluster LIPGENE-SU.VI.MAX participants using a Bayesian finite mixture model. A computationally efficient variable selection algorithm is incorporated, estimation is via a Gibbs sampling algorithm and an approximate BIC-MCMC criterion is developed to select the optimal model. Two clusters or sub-phenotypes ('healthy' and 'at risk') are uncovered. A small subset of variables is deemed discriminatory, which notably includes phenotypic and genotypic variables, highlighting the need to jointly consider both factors. Further, 7 years after the LIPGENE-SU.VI.MAX data were collected, participants underwent further analysis to diagnose presence or absence of the MetS. The two uncovered sub-phenotypes strongly correspond to the 7-year follow-up disease classification, highlighting the role of phenotypic and genotypic factors in the MetS and emphasising the potential utility of the clustering approach in early screening. Additionally, the ability of the proposed approach to define the uncertainty in sub-phenotype membership at the participant level is synonymous with the concepts of precision medicine and nutrition. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

The MINOS Experiment: Results and Prospects

DOE PAGES

Evans, J. J.

2013-01-01

Tmore » he MINOS experiment has used the world’s most powerful neutrino beam to make precision neutrino oscillation measurements. By observing the disappearance of muon neutrinos, MINOS has made the world’s most precise measurement of the larger neutrino mass splitting and has measured the neutrino mixing angle θ 23 . Using a dedicated antineutrino beam, MINOS has made the first direct precision measurements of the corresponding antineutrino parameters. A search for ν e and ν - e appearance has enabled a measurement of the mixing angle θ 13 . A measurement of the neutral-current interaction rate has confirmed oscillation between three active neutrino flavours. MINOS will continue as MINOS+ in an upgraded beam with higher energy and intensity, allowing precision tests of the three-flavour neutrino oscillation picture, in particular a very sensitive search for the existence of sterile neutrinos.« less

Real-Time PPP Based on the Coupling Estimation of Clock Bias and Orbit Error with Broadcast Ephemeris.

PubMed

Pan, Shuguo; Chen, Weirong; Jin, Xiaodong; Shi, Xiaofei; He, Fan

2015-07-22

Satellite orbit error and clock bias are the keys to precise point positioning (PPP). The traditional PPP algorithm requires precise satellite products based on worldwide permanent reference stations. Such an algorithm requires considerable work and hardly achieves real-time performance. However, real-time positioning service will be the dominant mode in the future. IGS is providing such an operational service (RTS) and there are also commercial systems like Trimble RTX in operation. On the basis of the regional Continuous Operational Reference System (CORS), a real-time PPP algorithm is proposed to apply the coupling estimation of clock bias and orbit error. The projection of orbit error onto the satellite-receiver range has the same effects on positioning accuracy with clock bias. Therefore, in satellite clock estimation, part of the orbit error can be absorbed by the clock bias and the effects of residual orbit error on positioning accuracy can be weakened by the evenly distributed satellite geometry. In consideration of the simple structure of pseudorange equations and the high precision of carrier-phase equations, the clock bias estimation method coupled with orbit error is also improved. Rovers obtain PPP results by receiving broadcast ephemeris and real-time satellite clock bias coupled with orbit error. By applying the proposed algorithm, the precise orbit products provided by GNSS analysis centers are rendered no longer necessary. On the basis of previous theoretical analysis, a real-time PPP system was developed. Some experiments were then designed to verify this algorithm. Experimental results show that the newly proposed approach performs better than the traditional PPP based on International GNSS Service (IGS) real-time products. The positioning accuracies of the rovers inside and outside the network are improved by 38.8% and 36.1%, respectively. The PPP convergence speeds are improved by up to 61.4% and 65.9%. The new approach can change the traditional PPP mode because of its advantages of independence, high positioning precision, and real-time performance. It could be an alternative solution for regional positioning service before global PPP service comes into operation.

Real-Time PPP Based on the Coupling Estimation of Clock Bias and Orbit Error with Broadcast Ephemeris

PubMed Central

Pan, Shuguo; Chen, Weirong; Jin, Xiaodong; Shi, Xiaofei; He, Fan

2015-01-01

Satellite orbit error and clock bias are the keys to precise point positioning (PPP). The traditional PPP algorithm requires precise satellite products based on worldwide permanent reference stations. Such an algorithm requires considerable work and hardly achieves real-time performance. However, real-time positioning service will be the dominant mode in the future. IGS is providing such an operational service (RTS) and there are also commercial systems like Trimble RTX in operation. On the basis of the regional Continuous Operational Reference System (CORS), a real-time PPP algorithm is proposed to apply the coupling estimation of clock bias and orbit error. The projection of orbit error onto the satellite-receiver range has the same effects on positioning accuracy with clock bias. Therefore, in satellite clock estimation, part of the orbit error can be absorbed by the clock bias and the effects of residual orbit error on positioning accuracy can be weakened by the evenly distributed satellite geometry. In consideration of the simple structure of pseudorange equations and the high precision of carrier-phase equations, the clock bias estimation method coupled with orbit error is also improved. Rovers obtain PPP results by receiving broadcast ephemeris and real-time satellite clock bias coupled with orbit error. By applying the proposed algorithm, the precise orbit products provided by GNSS analysis centers are rendered no longer necessary. On the basis of previous theoretical analysis, a real-time PPP system was developed. Some experiments were then designed to verify this algorithm. Experimental results show that the newly proposed approach performs better than the traditional PPP based on International GNSS Service (IGS) real-time products. The positioning accuracies of the rovers inside and outside the network are improved by 38.8% and 36.1%, respectively. The PPP convergence speeds are improved by up to 61.4% and 65.9%. The new approach can change the traditional PPP mode because of its advantages of independence, high positioning precision, and real-time performance. It could be an alternative solution for regional positioning service before global PPP service comes into operation. PMID:26205276

Mixed-Strategy Chance Constrained Optimal Control

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J.

2013-01-01

This paper presents a novel chance constrained optimal control (CCOC) algorithm that chooses a control action probabilistically. A CCOC problem is to find a control input that minimizes the expected cost while guaranteeing that the probability of violating a set of constraints is below a user-specified threshold. We show that a probabilistic control approach, which we refer to as a mixed control strategy, enables us to obtain a cost that is better than what deterministic control strategies can achieve when the CCOC problem is nonconvex. The resulting mixed-strategy CCOC problem turns out to be a convexification of the original nonconvex CCOC problem. Furthermore, we also show that a mixed control strategy only needs to "mix" up to two deterministic control actions in order to achieve optimality. Building upon an iterative dual optimization, the proposed algorithm quickly converges to the optimal mixed control strategy with a user-specified tolerance.

Auxiliary principle technique and iterative algorithm for a perturbed system of generalized multi-valued mixed quasi-equilibrium-like problems.

PubMed

Rahaman, Mijanur; Pang, Chin-Tzong; Ishtyak, Mohd; Ahmad, Rais

2017-01-01

In this article, we introduce a perturbed system of generalized mixed quasi-equilibrium-like problems involving multi-valued mappings in Hilbert spaces. To calculate the approximate solutions of the perturbed system of generalized multi-valued mixed quasi-equilibrium-like problems, firstly we develop a perturbed system of auxiliary generalized multi-valued mixed quasi-equilibrium-like problems, and then by using the celebrated Fan-KKM technique, we establish the existence and uniqueness of solutions of the perturbed system of auxiliary generalized multi-valued mixed quasi-equilibrium-like problems. By deploying an auxiliary principle technique and an existence result, we formulate an iterative algorithm for solving the perturbed system of generalized multi-valued mixed quasi-equilibrium-like problems. Lastly, we study the strong convergence analysis of the proposed iterative sequences under monotonicity and some mild conditions. These results are new and generalize some known results in this field.

A novel gene network inference algorithm using predictive minimum description length approach.

PubMed

Chaitankar, Vijender; Ghosh, Preetam; Perkins, Edward J; Gong, Ping; Deng, Youping; Zhang, Chaoyang

2010-05-28

Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold which defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we proposed a new inference algorithm which incorporated mutual information (MI), conditional mutual information (CMI) and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm was evaluated using both synthetic time series data sets and a biological time series data set for the yeast Saccharomyces cerevisiae. The benchmark quantities precision and recall were used as performance measures. The results show that the proposed algorithm produced less false edges and significantly improved the precision, as compared to the existing algorithm. For further analysis the performance of the algorithms was observed over different sizes of data. We have proposed a new algorithm that implements the PMDL principle for inferring gene regulatory networks from time series DNA microarray data that eliminates the need of a fine tuning parameter. The evaluation results obtained from both synthetic and actual biological data sets show that the PMDL principle is effective in determining the MI threshold and the developed algorithm improves precision of gene regulatory network inference. Based on the sensitivity analysis of all tested cases, an optimal CMI threshold value has been identified. Finally it was observed that the performance of the algorithms saturates at a certain threshold of data size.

Investigation of optical current transformer signal processing method based on an improved Kalman algorithm

NASA Astrophysics Data System (ADS)

Shen, Yan; Ge, Jin-ming; Zhang, Guo-qing; Yu, Wen-bin; Liu, Rui-tong; Fan, Wei; Yang, Ying-xuan

2018-01-01

This paper explores the problem of signal processing in optical current transformers (OCTs). Based on the noise characteristics of OCTs, such as overlapping signals, noise frequency bands, low signal-to-noise ratios, and difficulties in acquiring statistical features of noise power, an improved standard Kalman filtering algorithm was proposed for direct current (DC) signal processing. The state-space model of the OCT DC measurement system is first established, and then mixed noise can be processed by adding mixed noise into measurement and state parameters. According to the minimum mean squared error criterion, state predictions and update equations of the improved Kalman algorithm could be deduced based on the established model. An improved central difference Kalman filter was proposed for alternating current (AC) signal processing, which improved the sampling strategy and noise processing of colored noise. Real-time estimation and correction of noise were achieved by designing AC and DC noise recursive filters. Experimental results show that the improved signal processing algorithms had a good filtering effect on the AC and DC signals with mixed noise of OCT. Furthermore, the proposed algorithm was able to achieve real-time correction of noise during the OCT filtering process.

Development of homotopy algorithms for fixed-order mixed H2/H(infinity) controller synthesis

NASA Technical Reports Server (NTRS)

Whorton, M.; Buschek, H.; Calise, A. J.

1994-01-01

A major difficulty associated with H-infinity and mu-synthesis methods is the order of the resulting compensator. Whereas model and/or controller reduction techniques are sometimes applied, performance and robustness properties are not preserved. By directly constraining compensator order during the optimization process, these properties are better preserved, albeit at the expense of computational complexity. This paper presents a novel homotopy algorithm to synthesize fixed-order mixed H2/H-infinity compensators. Numerical results are presented for a four-disk flexible structure to evaluate the efficiency of the algorithm.

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

PubMed Central

Neftci, Emre O.; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning. PMID:28680387

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines.

PubMed

Neftci, Emre O; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

Application of multiple signal classification algorithm to frequency estimation in coherent dual-frequency lidar

NASA Astrophysics Data System (ADS)

Li, Ruixiao; Li, Kun; Zhao, Changming

2018-01-01

Coherent dual-frequency Lidar (CDFL) is a new development of Lidar which dramatically enhances the ability to decrease the influence of atmospheric interference by using dual-frequency laser to measure the range and velocity with high precision. Based on the nature of CDFL signals, we propose to apply the multiple signal classification (MUSIC) algorithm in place of the fast Fourier transform (FFT) to estimate the phase differences in dual-frequency Lidar. In the presence of Gaussian white noise, the simulation results show that the signal peaks are more evident when using MUSIC algorithm instead of FFT in condition of low signal-noise-ratio (SNR), which helps to improve the precision of detection on range and velocity, especially for the long distance measurement systems.

Influence of Fiber Bragg Grating Spectrum Degradation on the Performance of Sensor Interrogation Algorithms

PubMed Central

Lamberti, Alfredo; Vanlanduit, Steve; De Pauw, Ben; Berghmans, Francis

2014-01-01

The working principle of fiber Bragg grating (FBG) sensors is mostly based on the tracking of the Bragg wavelength shift. To accomplish this task, different algorithms have been proposed, from conventional maximum and centroid detection algorithms to more recently-developed correlation-based techniques. Several studies regarding the performance of these algorithms have been conducted, but they did not take into account spectral distortions, which appear in many practical applications. This paper addresses this issue and analyzes the performance of four different wavelength tracking algorithms (maximum detection, centroid detection, cross-correlation and fast phase-correlation) when applied to distorted FBG spectra used for measuring dynamic loads. Both simulations and experiments are used for the analyses. The dynamic behavior of distorted FBG spectra is simulated using the transfer-matrix approach, and the amount of distortion of the spectra is quantified using dedicated distortion indices. The algorithms are compared in terms of achievable precision and accuracy. To corroborate the simulation results, experiments were conducted using three FBG sensors glued on a steel plate and subjected to a combination of transverse force and vibration loads. The analysis of the results showed that the fast phase-correlation algorithm guarantees the best combination of versatility, precision and accuracy. PMID:25521386

Bit Grooming: Statistically accurate precision-preserving quantization with compression, evaluated in the netCDF operators (NCO, v4.4.8+)

DOE PAGES

Zender, Charles S.

2016-09-19

Geoscientific models and measurements generate false precision (scientifically meaningless data bits) that wastes storage space. False precision can mislead (by implying noise is signal) and be scientifically pointless, especially for measurements. By contrast, lossy compression can be both economical (save space) and heuristic (clarify data limitations) without compromising the scientific integrity of data. Data quantization can thus be appropriate regardless of whether space limitations are a concern. We introduce, implement, and characterize a new lossy compression scheme suitable for IEEE floating-point data. Our new Bit Grooming algorithm alternately shaves (to zero) and sets (to one) the least significant bits ofmore » consecutive values to preserve a desired precision. This is a symmetric, two-sided variant of an algorithm sometimes called Bit Shaving that quantizes values solely by zeroing bits. Our variation eliminates the artificial low bias produced by always zeroing bits, and makes Bit Grooming more suitable for arrays and multi-dimensional fields whose mean statistics are important. Bit Grooming relies on standard lossless compression to achieve the actual reduction in storage space, so we tested Bit Grooming by applying the DEFLATE compression algorithm to bit-groomed and full-precision climate data stored in netCDF3, netCDF4, HDF4, and HDF5 formats. Bit Grooming reduces the storage space required by initially uncompressed and compressed climate data by 25–80 and 5–65 %, respectively, for single-precision values (the most common case for climate data) quantized to retain 1–5 decimal digits of precision. The potential reduction is greater for double-precision datasets. When used aggressively (i.e., preserving only 1–2 digits), Bit Grooming produces storage reductions comparable to other quantization techniques such as Linear Packing. Unlike Linear Packing, whose guaranteed precision rapidly degrades within the relatively narrow dynamic range of values that it can compress, Bit Grooming guarantees the specified precision throughout the full floating-point range. Data quantization by Bit Grooming is irreversible (i.e., lossy) yet transparent, meaning that no extra processing is required by data users/readers. Hence Bit Grooming can easily reduce data storage volume without sacrificing scientific precision or imposing extra burdens on users.« less

Hysteresis modeling of magnetic shape memory alloy actuator based on Krasnosel'skii-Pokrovskii model.

PubMed

Zhou, Miaolei; Wang, Shoubin; Gao, Wei

2013-01-01

As a new type of intelligent material, magnetically shape memory alloy (MSMA) has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP) model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator.

Hysteresis Modeling of Magnetic Shape Memory Alloy Actuator Based on Krasnosel'skii-Pokrovskii Model

PubMed Central

Wang, Shoubin; Gao, Wei

2013-01-01

As a new type of intelligent material, magnetically shape memory alloy (MSMA) has a good performance in its applications in the actuator manufacturing. Compared with traditional actuators, MSMA actuator has the advantages as fast response and large deformation; however, the hysteresis nonlinearity of the MSMA actuator restricts its further improving of control precision. In this paper, an improved Krasnosel'skii-Pokrovskii (KP) model is used to establish the hysteresis model of MSMA actuator. To identify the weighting parameters of the KP operators, an improved gradient correction algorithm and a variable step-size recursive least square estimation algorithm are proposed in this paper. In order to demonstrate the validity of the proposed modeling approach, simulation experiments are performed, simulations with improved gradient correction algorithm and variable step-size recursive least square estimation algorithm are studied, respectively. Simulation results of both identification algorithms demonstrate that the proposed modeling approach in this paper can establish an effective and accurate hysteresis model for MSMA actuator, and it provides a foundation for improving the control precision of MSMA actuator. PMID:23737730

Groverian measure of entanglement for mixed states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shapira, Daniel; Shimoni, Yishai; Biham, Ofer

2006-04-15

The Groverian entanglement measure, introduced earlier for pure quantum states of multiple qubits [O. Biham, M.A. Nielsen, and T. Osborne, Phys. Rev. A 65, 062312 (2002)], is generalized to the case of mixed states. The Groverian measure of a mixed state of n qubits is obtained by a purification procedure into a pure state of 2n qubits, followed by an optimization process, before the resulting state is fed into Grover's search algorithm. It is expressed in terms of the maximal success probability of the algorithm and in this sense provides an operational measure of entanglement.

Improving Mixed-phase Cloud Parameterization in Climate Model with the ACRF Measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zhien

Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentrationmore » retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations of mixed-phase cloud simulations by CAM5 were performed. Measurement results indicate that ice concentrations control stratiform mixed-phase cloud properties. The improvement of ice concentration parameterization in the CAM5 was done in close collaboration with Dr. Xiaohong Liu, PNNL (now at University of Wyoming).« less

A Parameter Subset Selection Algorithm for Mixed-Effects Models

DOE PAGES

Schmidt, Kathleen L.; Smith, Ralph C.

2016-01-01

Mixed-effects models are commonly used to statistically model phenomena that include attributes associated with a population or general underlying mechanism as well as effects specific to individuals or components of the general mechanism. This can include individual effects associated with data from multiple experiments. However, the parameterizations used to incorporate the population and individual effects are often unidentifiable in the sense that parameters are not uniquely specified by the data. As a result, the current literature focuses on model selection, by which insensitive parameters are fixed or removed from the model. Model selection methods that employ information criteria are applicablemore » to both linear and nonlinear mixed-effects models, but such techniques are limited in that they are computationally prohibitive for large problems due to the number of possible models that must be tested. To limit the scope of possible models for model selection via information criteria, we introduce a parameter subset selection (PSS) algorithm for mixed-effects models, which orders the parameters by their significance. In conclusion, we provide examples to verify the effectiveness of the PSS algorithm and to test the performance of mixed-effects model selection that makes use of parameter subset selection.« less

Evaluation schemes for video and image anomaly detection algorithms

NASA Astrophysics Data System (ADS)

Parameswaran, Shibin; Harguess, Josh; Barngrover, Christopher; Shafer, Scott; Reese, Michael

2016-05-01

Video anomaly detection is a critical research area in computer vision. It is a natural first step before applying object recognition algorithms. There are many algorithms that detect anomalies (outliers) in videos and images that have been introduced in recent years. However, these algorithms behave and perform differently based on differences in domains and tasks to which they are subjected. In order to better understand the strengths and weaknesses of outlier algorithms and their applicability in a particular domain/task of interest, it is important to measure and quantify their performance using appropriate evaluation metrics. There are many evaluation metrics that have been used in the literature such as precision curves, precision-recall curves, and receiver operating characteristic (ROC) curves. In order to construct these different metrics, it is also important to choose an appropriate evaluation scheme that decides when a proposed detection is considered a true or a false detection. Choosing the right evaluation metric and the right scheme is very critical since the choice can introduce positive or negative bias in the measuring criterion and may favor (or work against) a particular algorithm or task. In this paper, we review evaluation metrics and popular evaluation schemes that are used to measure the performance of anomaly detection algorithms on videos and imagery with one or more anomalies. We analyze the biases introduced by these by measuring the performance of an existing anomaly detection algorithm.

Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees.

PubMed

Fokkema, M; Smits, N; Zeileis, A; Hothorn, T; Kelderman, H

2017-10-25

Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.

An optimized BP neural network based on genetic algorithm for static decoupling of a six-axis force/torque sensor

NASA Astrophysics Data System (ADS)

Fu, Liyue; Song, Aiguo

2018-02-01

In order to improve the measurement precision of 6-axis force/torque sensor for robot, BP decoupling algorithm optimized by GA (GA-BP algorithm) is proposed in this paper. The weights and thresholds of a BP neural network with 6-10-6 topology are optimized by GA to develop decouple a six-axis force/torque sensor. By comparison with other traditional decoupling algorithm, calculating the pseudo-inverse matrix of calibration and classical BP algorithm, the decoupling results validate the good decoupling performance of GA-BP algorithm and the coupling errors are reduced.

Assessment of Mixed-Layer Height Estimation from Single-wavelength Ceilometer Profiles

PubMed Central

Knepp, Travis N.; Szykman, James J.; Long, Russell; Duvall, Rachelle M.; Krug, Jonathan; Beaver, Melinda; Cavender, Kevin; Kronmiller, Keith; Wheeler, Michael; Delgado, Ruben; Hoff, Raymond; Berkoff, Timothy; Olson, Erik; Clark, Richard; Wolfe, Daniel; Van Gilst, David; Neil, Doreen

2018-01-01

Differing boundary/mixed-layer height measurement methods were assessed in moderately-polluted and clean environments, with a focus on the Vaisala CL51 ceilometer. This intercomparison was performed as part of ongoing measurements at the Chemistry And Physics of the Atmospheric Boundary Layer Experiment (CAPABLE) site in Hampton, Virginia and during the 2014 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign that took place in and around Denver, Colorado. We analyzed CL51 data that were collected via two different methods (BLView software, which applied correction factors, and simple terminal emulation logging) to determine the impact of data collection methodology. Further, we evaluated the STRucture of the ATmosphere (STRAT) algorithm as an open-source alternative to BLView (note that the current work presents an evaluation of the BLView and STRAT algorithms and does not intend to act as a validation of either). Filtering criteria were defined according to the change in mixed-layer height (MLH) distributions for each instrument and algorithm and were applied throughout the analysis to remove high-frequency fluctuations from the MLH retrievals. Of primary interest was determining how the different data-collection methodologies and algorithms compare to each other and to radiosonde-derived boundary-layer heights when deployed as part of a larger instrument network. We determined that data-collection methodology is not as important as the processing algorithm and that much of the algorithm differences might be driven by impacts of local meteorology and precipitation events that pose algorithm difficulties. The results of this study show that a common processing algorithm is necessary for LIght Detection And Ranging (LIDAR)-based MLH intercomparisons, and ceilometer-network operation and that sonde-derived boundary layer heights are higher (10–15% at mid-day) than LIDAR-derived mixed-layer heights. We show that averaging the retrieved MLH to 1-hour resolution (an appropriate time scale for a priori data model initialization) significantly improved correlation between differing instruments and differing algorithms. PMID:29682087

Improved algorithm of ray tracing in ICF cryogenic targets

NASA Astrophysics Data System (ADS)

Zhang, Rui; Yang, Yongying; Ling, Tong; Jiang, Jiabin

2016-10-01

The high precision ray tracing inside inertial confinement fusion (ICF) cryogenic targets plays an important role in the reconstruction of the three-dimensional density distribution by algebraic reconstruction technique (ART) algorithm. The traditional Runge-Kutta methods, which is restricted by the precision of the grid division and the step size of ray tracing, cannot make an accurate calculation in the case of refractive index saltation. In this paper, we propose an improved algorithm of ray tracing based on the Runge-Kutta methods and Snell's law of refraction to achieve high tracing precision. On the boundary of refractive index, we apply Snell's law of refraction and contact point search algorithm to ensure accuracy of the simulation. Inside the cryogenic target, the combination of the Runge-Kutta methods and self-adaptive step algorithm are employed for computation. The original refractive index data, which is used to mesh the target, can be obtained by experimental measurement or priori refractive index distribution function. A finite differential method is performed to calculate the refractive index gradient of mesh nodes, and the distance weighted average interpolation methods is utilized to obtain refractive index and gradient of each point in space. In the simulation, we take ideal ICF target, Luneberg lens and Graded index rod as simulation model to calculate the spot diagram and wavefront map. Compared the simulation results to Zemax, it manifests that the improved algorithm of ray tracing based on the fourth-order Runge-Kutta methods and Snell's law of refraction exhibits high accuracy. The relative error of the spot diagram is 0.2%, and the peak-to-valley (PV) error and the root-mean-square (RMS) error of the wavefront map is less than λ/35 and λ/100, correspondingly.

Detecting Nano-Scale Vibrations in Rotating Devices by Using Advanced Computational Methods

PubMed Central

del Toro, Raúl M.; Haber, Rodolfo E.; Schmittdiel, Michael C.

2010-01-01

This paper presents a computational method for detecting vibrations related to eccentricity in ultra precision rotation devices used for nano-scale manufacturing. The vibration is indirectly measured via a frequency domain analysis of the signal from a piezoelectric sensor attached to the stationary component of the rotating device. The algorithm searches for particular harmonic sequences associated with the eccentricity of the device rotation axis. The detected sequence is quantified and serves as input to a regression model that estimates the eccentricity. A case study presents the application of the computational algorithm during precision manufacturing processes. PMID:22399918

Precise calculation of the local pressure tensor in Cartesian and spherical coordinates in LAMMPS

NASA Astrophysics Data System (ADS)

Nakamura, Takenobu; Kawamoto, Shuhei; Shinoda, Wataru

2015-05-01

An accurate and efficient algorithm for calculating the 3D pressure field has been developed and implemented in the open-source molecular dynamics package, LAMMPS. Additionally, an algorithm to compute the pressure profile along the radial direction in spherical coordinates has also been implemented. The latter is particularly useful for systems showing a spherical symmetry such as micelles and vesicles. These methods yield precise pressure fields based on the Irving-Kirkwood contour integration and are particularly useful for biomolecular force fields. The present methods are applied to several systems including a buckled membrane and a vesicle.

An improved conscan algorithm based on a Kalman filter

NASA Technical Reports Server (NTRS)

Eldred, D. B.

1994-01-01

Conscan is commonly used by DSN antennas to allow adaptive tracking of a target whose position is not precisely known. This article describes an algorithm that is based on a Kalman filter and is proposed to replace the existing fast Fourier transform based (FFT-based) algorithm for conscan. Advantages of this algorithm include better pointing accuracy, continuous update information, and accommodation of missing data. Additionally, a strategy for adaptive selection of the conscan radius is proposed. The performance of the algorithm is illustrated through computer simulations and compared to the FFT algorithm. The results show that the Kalman filter algorithm is consistently superior.

A preference for some types of complexity comment on "perceived beauty of random texture patterns: A preference for complexity".

PubMed

Gauvrit, Nicolas; Soler-Toscano, Fernando; Guida, Alessandro

2017-03-01

In two experiments, Friedenberg and Liby (2016) studied how a diversity of complexity estimates such as density, number of blocks, GIF compression rate and edge length impact the perception of beauty of semi-random two-dimensional patterns. They concluded that aesthetics ratings are positively linked with GIF compression metrics and edge length, but not with the number of blocks. They also found an inverse U-shaped link between aesthetic judgments and density. These mixed results originate in the variety of metrics used to estimate what is loosely called "complexity" in psychology and indeed refers to conflicting notions. Here, we reanalyze their data adding two more conventional and normative mathematical measures of complexity: entropy and algorithmic complexity. We show that their results can be interpreted as an aesthetic preference for low redundancy, balanced patterns and "crooked" figures, but not for high algorithmic complexity. We conclude that participants tend to have a preference for some types of complexity, but not for all. These findings may help understand divergent results in the study of perceived beauty and complexity, and illustrate the need to specify the notion of complexity used in psychology. The field would certainly benefit from a precise taxonomy of complexity measures. Copyright © 2017 Elsevier B.V. All rights reserved.

Detection of Soil Nitrogen Using Near Infrared Sensors Based on Soil Pretreatment and Algorithms

PubMed Central

Nie, Pengcheng; Dong, Tao; He, Yong; Qu, Fangfang

2017-01-01

Soil nitrogen content is one of the important growth nutrient parameters of crops. It is a prerequisite for scientific fertilization to accurately grasp soil nutrient information in precision agriculture. The information about nutrients such as nitrogen in the soil can be obtained quickly by using a near-infrared sensor. The data can be analyzed in the detection process, which is nondestructive and non-polluting. In order to investigate the effect of soil pretreatment on nitrogen content by near infrared sensor, 16 nitrogen concentrations were mixed with soil and the soil samples were divided into three groups with different pretreatment. The first group of soil samples with strict pretreatment were dried, ground, sieved and pressed. The second group of soil samples were dried and ground. The third group of soil samples were simply dried. Three linear different modeling methods are used to analyze the spectrum, including partial least squares (PLS), uninformative variable elimination (UVE), competitive adaptive reweighted algorithm (CARS). The model of nonlinear partial least squares which supports vector machine (LS-SVM) is also used to analyze the soil reflectance spectrum. The results show that the soil samples with strict pretreatment have the best accuracy in predicting nitrogen content by near-infrared sensor, and the pretreatment method is suitable for practical application. PMID:28492480

Wrap spring clutch syringe ram and frit mixer

DOEpatents

Simpson, Frank B.

2006-07-25

A wrap spring clutch syringe ram pushes at least one syringe with virtually instantaneous starting and stopping, and with constant motion at a defined velocity during the intervening push. The wrap spring clutch syringe ram includes an electric motor, a computer, a flywheel, a wrap spring clutch, a precision lead screw, a slide platform, and syringe reservoirs, a mixing chamber, and a reaction incubation tube. The electric motor drives a flywheel and the wrap spring clutch couples the precision lead screw to the flywheel when a computer enables a solenoid of the wrap spring clutch. The precision lead screw drives a precision slide which causes syringes to supply a portion of solution into the mixing chamber and the incubation tube. The wrap spring clutch syringe ram is designed to enable the quantitative study of solution phase chemical and biochemical reactions, particularly those reactions that occur on the subsecond time scale.

Modified automatic R-peak detection algorithm for patients with epilepsy using a portable electrocardiogram recorder.

PubMed

Jeppesen, J; Beniczky, S; Fuglsang Frederiksen, A; Sidenius, P; Johansen, P

2017-07-01

Earlier studies have shown that short term heart rate variability (HRV) analysis of ECG seems promising for detection of epileptic seizures. A precise and accurate automatic R-peak detection algorithm is a necessity in a real-time, continuous measurement of HRV, in a portable ECG device. We used the portable CE marked ePatch® heart monitor to record the ECG of 14 patients, who were enrolled in the videoEEG long term monitoring unit for clinical workup of epilepsy. Recordings of the first 7 patients were used as training set of data for the R-peak detection algorithm and the recordings of the last 7 patients (467.6 recording hours) were used to test the performance of the algorithm. We aimed to modify an existing QRS-detection algorithm to a more precise R-peak detection algorithm to avoid the possible jitter Qand S-peaks can create in the tachogram, which causes error in short-term HRVanalysis. The proposed R-peak detection algorithm showed a high sensitivity (Se = 99.979%) and positive predictive value (P+ = 99.976%), which was comparable with a previously published QRS-detection algorithm for the ePatch® ECG device, when testing the same dataset. The novel R-peak detection algorithm designed to avoid jitter has very high sensitivity and specificity and thus is a suitable tool for a robust, fast, real-time HRV-analysis in patients with epilepsy, creating the possibility for real-time seizure detection for these patients.

A Gaussian Mixture Model for Nulling Pulsars

NASA Astrophysics Data System (ADS)

Kaplan, D. L.; Swiggum, J. K.; Fichtenbauer, T. D. J.; Vallisneri, M.

2018-03-01

The phenomenon of pulsar nulling—where pulsars occasionally turn off for one or more pulses—provides insight into pulsar-emission mechanisms and the processes by which pulsars turn off when they cross the “death line.” However, while ever more pulsars are found that exhibit nulling behavior, the statistical techniques used to measure nulling are biased, with limited utility and precision. In this paper, we introduce an improved algorithm, based on Gaussian mixture models, for measuring pulsar nulling behavior. We demonstrate this algorithm on a number of pulsars observed as part of a larger sample of nulling pulsars, and show that it performs considerably better than existing techniques, yielding better precision and no bias. We further validate our algorithm on simulated data. Our algorithm is widely applicable to a large number of pulsars even if they do not show obvious nulls. Moreover, it can be used to derive nulling probabilities of nulling for individual pulses, which can be used for in-depth studies.

Assessment of Gamma-Ray-Spectra Analysis Method Utilizing the Fireworks Algorithm for Various Error Measures

DOE PAGES

Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

2018-01-01

The analysis of measured data plays a significant role in enhancing nuclear nonproliferation mainly by inferring the presence of patterns associated with special nuclear materials. Among various types of measurements, gamma-ray spectra is the widest utilized type of data in nonproliferation applications. In this paper, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. In particular, FWA is utilized to fit a set of known signatures to a measured spectrum by optimizing an objective function, where non-zero coefficients express the detected signatures. FWA is tested on a set of experimentallymore » obtained measurements optimizing various objective functions—MSE, RMSE, Theil-2, MAE, MAPE, MAP—with results exhibiting its potential in providing highly accurate and precise signature detection. Finally and furthermore, FWA is benchmarked against genetic algorithms and multiple linear regression, showing its superiority over those algorithms regarding precision with respect to MAE, MAPE, and MAP measures.« less

Parameters Identification for Photovoltaic Module Based on an Improved Artificial Fish Swarm Algorithm

PubMed Central

Wang, Hong-Hua

2014-01-01

A precise mathematical model plays a pivotal role in the simulation, evaluation, and optimization of photovoltaic (PV) power systems. Different from the traditional linear model, the model of PV module has the features of nonlinearity and multiparameters. Since conventional methods are incapable of identifying the parameters of PV module, an excellent optimization algorithm is required. Artificial fish swarm algorithm (AFSA), originally inspired by the simulation of collective behavior of real fish swarms, is proposed to fast and accurately extract the parameters of PV module. In addition to the regular operation, a mutation operator (MO) is designed to enhance the searching performance of the algorithm. The feasibility of the proposed method is demonstrated by various parameters of PV module under different environmental conditions, and the testing results are compared with other studied methods in terms of final solutions and computational time. The simulation results show that the proposed method is capable of obtaining higher parameters identification precision. PMID:25243233

Stochastic Models of Polymer Systems

DTIC Science & Technology

2016-01-01

SECURITY CLASSIFICATION OF: The stochastic gradient decent algorithm is the now the "algorithm of choice" for very large machine learning problems...information about the behavior of the algorithm. At the same time, we were also able to formulate various acceleration techniques in precise math terms... gradient decent, REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 10. SPONSOR/MONITOR’S ACRONYM(S) ARO 8. PERFORMING

Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR

PubMed Central

MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali

2017-01-01

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms. PMID:28979308

Sequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR.

PubMed

MotieGhader, Habib; Gharaghani, Sajjad; Masoudi-Sobhanzadeh, Yosef; Masoudi-Nejad, Ali

2017-01-01

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as GA, PSO, ACO and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR feature selection are proposed. SGALA algorithm uses advantages of Genetic algorithm and Learning Automata sequentially and the MGALA algorithm uses advantages of Genetic Algorithm and Learning Automata simultaneously. We applied our proposed algorithms to select the minimum possible number of features from three different datasets and also we observed that the MGALA and SGALA algorithms had the best outcome independently and in average compared to other feature selection algorithms. Through comparison of our proposed algorithms, we deduced that the rate of convergence to optimal result in MGALA and SGALA algorithms were better than the rate of GA, ACO, PSO and LA algorithms. In the end, the results of GA, ACO, PSO, LA, SGALA, and MGALA algorithms were applied as the input of LS-SVR model and the results from LS-SVR models showed that the LS-SVR model had more predictive ability with the input from SGALA and MGALA algorithms than the input from all other mentioned algorithms. Therefore, the results have corroborated that not only is the predictive efficiency of proposed algorithms better, but their rate of convergence is also superior to the all other mentioned algorithms.

Fast Mix Table Construction for Material Discretization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Seth R

2013-01-01

An effective hybrid Monte Carlo--deterministic implementation typically requires the approximation of a continuous geometry description with a discretized piecewise-constant material field. The inherent geometry discretization error can be reduced somewhat by using material mixing, where multiple materials inside a discrete mesh voxel are homogenized. Material mixing requires the construction of a ``mix table,'' which stores the volume fractions in every mixture so that multiple voxels with similar compositions can reference the same mixture. Mix table construction is a potentially expensive serial operation for large problems with many materials and voxels. We formulate an efficient algorithm to construct a sparse mix table inmore » $$O(\\text{number of voxels}\\times \\log \\text{number of mixtures})$$ time. The new algorithm is implemented in ADVANTG and used to discretize continuous geometries onto a structured Cartesian grid. When applied to an end-of-life MCNP model of the High Flux Isotope Reactor with 270 distinct materials, the new method improves the material mixing time by a factor of 100 compared to a naive mix table implementation.« less

Scalability problems of simple genetic algorithms.

PubMed

Thierens, D

1999-01-01

Scalable evolutionary computation has become an intensively studied research topic in recent years. The issue of scalability is predominant in any field of algorithmic design, but it became particularly relevant for the design of competent genetic algorithms once the scalability problems of simple genetic algorithms were understood. Here we present some of the work that has aided in getting a clear insight in the scalability problems of simple genetic algorithms. Particularly, we discuss the important issue of building block mixing. We show how the need for mixing places a boundary in the GA parameter space that, together with the boundary from the schema theorem, delimits the region where the GA converges reliably to the optimum in problems of bounded difficulty. This region shrinks rapidly with increasing problem size unless the building blocks are tightly linked in the problem coding structure. In addition, we look at how straightforward extensions of the simple genetic algorithm-namely elitism, niching, and restricted mating are not significantly improving the scalability problems.

Precision half-life measurement of 11C: The most precise mirror transition F t value

NASA Astrophysics Data System (ADS)

Valverde, A. A.; Brodeur, M.; Ahn, T.; Allen, J.; Bardayan, D. W.; Becchetti, F. D.; Blankstein, D.; Brown, G.; Burdette, D. P.; Frentz, B.; Gilardy, G.; Hall, M. R.; King, S.; Kolata, J. J.; Long, J.; Macon, K. T.; Nelson, A.; O'Malley, P. D.; Skulski, M.; Strauss, S. Y.; Vande Kolk, B.

2018-03-01

Background: The precise determination of the F t value in T =1 /2 mixed mirror decays is an important avenue for testing the standard model of the electroweak interaction through the determination of Vu d in nuclear β decays. 11C is an interesting case, as its low mass and small QE C value make it particularly sensitive to violations of the conserved vector current hypothesis. The present dominant source of uncertainty in the 11CF t value is the half-life. Purpose: A high-precision measurement of the 11C half-life was performed, and a new world average half-life was calculated. Method: 11C was created by transfer reactions and separated using the TwinSol facility at the Nuclear Science Laboratory at the University of Notre Dame. It was then implanted into a tantalum foil, and β counting was used to determine the half-life. Results: The new half-life, t1 /2=1220.27 (26 ) s, is consistent with the previous values but significantly more precise. A new world average was calculated, t1/2 world=1220.41 (32 ) s, and a new estimate for the Gamow-Teller to Fermi mixing ratio ρ is presented along with standard model correlation parameters. Conclusions: The new 11C world average half-life allows the calculation of a F tmirror value that is now the most precise value for all superallowed mixed mirror transitions. This gives a strong impetus for an experimental determination of ρ , to allow for the determination of Vu d from this decay.

A novel algorithm for detecting active propulsion in wheelchair users following spinal cord injury.

PubMed

Popp, Werner L; Brogioli, Michael; Leuenberger, Kaspar; Albisser, Urs; Frotzler, Angela; Curt, Armin; Gassert, Roger; Starkey, Michelle L

2016-03-01

Physical activity in wheelchair-bound individuals can be assessed by monitoring their mobility as this is one of the most intense upper extremity activities they perform. Current accelerometer-based approaches for describing wheelchair mobility do not distinguish between self- and attendant-propulsion and hence may overestimate total physical activity. The aim of this study was to develop and validate an inertial measurement unit based algorithm to monitor wheel kinematics and the type of wheelchair propulsion (self- or attendant-) within a "real-world" situation. Different sensor set-ups were investigated, ranging from a high precision set-up including four sensor modules with a relatively short measurement duration of 24 h, to a less precise set-up with only one module attached at the wheel exceeding one week of measurement because the gyroscope of the sensor was turned off. The "high-precision" algorithm distinguished self- and attendant-propulsion with accuracy greater than 93% whilst the long-term measurement set-up showed an accuracy of 82%. The estimation accuracy of kinematic parameters was greater than 97% for both set-ups. The possibility of having different sensor set-ups allows the use of the inertial measurement units as high precision tools for researchers as well as unobtrusive and simple tools for manual wheelchair users. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Algorithm of dynamic regulation of a system of duct, for a high accuracy climatic system

NASA Astrophysics Data System (ADS)

Arbatskiy, A. A.; Afonina, G. N.; Glazov, V. S.

2017-11-01

Currently, major part of climatic system, are stationary in projected mode only. At the same time, many modern industrial sites, require constant or periodical changes in technological process. That is 80% of the time, the industrial site is not require ventilation system in projected mode and high precision of climatic parameters must maintain. While that not constantly is in use for climatic systems, which use in parallel for different rooms, we will be have a problem for balance of duct system. For this problem, was created the algorithm for quantity regulation, with minimal changes. Dynamic duct system: Developed of parallel control system of air balance, with high precision of climatic parameters. The Algorithm provide a permanent pressure in main duct, in different a flow of air. Therefore, the ending devises air flow have only one parameter for regulation - flaps open area. Precision of regulation increase and the climatic system provide high precision for temperature and humidity (0,5C for temperature, 5% for relative humidity). Result: The research has been made in CFD-system - PHOENICS. Results for velocity of air in duct, for pressure of air in duct for different operation mode, has been obtained. Equation for air valves positions, with different parameters for climate in room’s, has been obtained. Energy saving potential for dynamic duct system, for different types of a rooms, has been calculated.

Mixed-initiative control of intelligent systems

NASA Technical Reports Server (NTRS)

Borchardt, G. C.

1987-01-01

Mixed-initiative user interfaces provide a means by which a human operator and an intelligent system may collectively share the task of deciding what to do next. Such interfaces are important to the effective utilization of real-time expert systems as assistants in the execution of critical tasks. Presented here is the Incremental Inference algorithm, a symbolic reasoning mechanism based on propositional logic and suited to the construction of mixed-initiative interfaces. The algorithm is similar in some respects to the Truth Maintenance System, but replaces the notion of 'justifications' with a notion of recency, allowing newer values to override older values yet permitting various interested parties to refresh these values as they become older and thus more vulnerable to change. A simple example is given of the use of the Incremental Inference algorithm plus an overview of the integration of this mechanism within the SPECTRUM expert system for geological interpretation of imaging spectrometer data.

Advanced scatter search approach and its application in a sequencing problem of mixed-model assembly lines in a case company

NASA Astrophysics Data System (ADS)

Liu, Qiong; Wang, Wen-xi; Zhu, Ke-ren; Zhang, Chao-yong; Rao, Yun-qing

2014-11-01

Mixed-model assembly line sequencing is significant in reducing the production time and overall cost of production. To improve production efficiency, a mathematical model aiming simultaneously to minimize overtime, idle time and total set-up costs is developed. To obtain high-quality and stable solutions, an advanced scatter search approach is proposed. In the proposed algorithm, a new diversification generation method based on a genetic algorithm is presented to generate a set of potentially diverse and high-quality initial solutions. Many methods, including reference set update, subset generation, solution combination and improvement methods, are designed to maintain the diversification of populations and to obtain high-quality ideal solutions. The proposed model and algorithm are applied and validated in a case company. The results indicate that the proposed advanced scatter search approach is significant for mixed-model assembly line sequencing in this company.

Image encryption algorithm based on multiple mixed hash functions and cyclic shift

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Zhu, Xiaoqiang; Wu, Xiangjun; Zhang, Yingqian

2018-08-01

This paper proposes a new one-time pad scheme for chaotic image encryption that is based on the multiple mixed hash functions and the cyclic-shift function. The initial value is generated using both information of the plaintext image and the chaotic sequences, which are calculated from the SHA1 and MD5 hash algorithms. The scrambling sequences are generated by the nonlinear equations and logistic map. This paper aims to improve the deficiencies of traditional Baptista algorithms and its improved algorithms. We employ the cyclic-shift function and piece-wise linear chaotic maps (PWLCM), which give each shift number the characteristics of chaos, to diffuse the image. Experimental results and security analysis show that the new scheme has better security and can resist common attacks.

The PX-EM algorithm for fast stable fitting of Henderson's mixed model

PubMed Central

Foulley, Jean-Louis; Van Dyk, David A

2000-01-01

This paper presents procedures for implementing the PX-EM algorithm of Liu, Rubin and Wu to compute REML estimates of variance covariance components in Henderson's linear mixed models. The class of models considered encompasses several correlated random factors having the same vector length e.g., as in random regression models for longitudinal data analysis and in sire-maternal grandsire models for genetic evaluation. Numerical examples are presented to illustrate the procedures. Much better results in terms of convergence characteristics (number of iterations and time required for convergence) are obtained for PX-EM relative to the basic EM algorithm in the random regression. PMID:14736399

Robust Flight Path Determination for Mars Precision Landing Using Genetic Algorithms

NASA Technical Reports Server (NTRS)

Bayard, David S.; Kohen, Hamid

1997-01-01

This paper documents the application of genetic algorithms (GAs) to the problem of robust flight path determination for Mars precision landing. The robust flight path problem is defined here as the determination of the flight path which delivers a low-lift open-loop controlled vehicle to its desired final landing location while minimizing the effect of perturbations due to uncertainty in the atmospheric model and entry conditions. The genetic algorithm was capable of finding solutions which reduced the landing error from 111 km RMS radial (open-loop optimal) to 43 km RMS radial (optimized with respect to perturbations) using 200 hours of computation on an Ultra-SPARC workstation. Further reduction in the landing error is possible by going to closed-loop control which can utilize the GA optimized paths as nominal trajectories for linearization.

Localization algorithms for micro-channel x-ray telescope on board SVOM space mission

NASA Astrophysics Data System (ADS)

Gosset, L.; Götz, D.; Osborne, J.; Willingale, R.

2016-07-01

SVOM is a French-Chinese space mission to be launched in 2021, whose goal is the study of Gamma-Ray Bursts, the most powerful stellar explosions in the Universe. The Micro-channel X-ray Telescope (MXT) is an X-ray focusing telescope, on board SVOM, with a field of view of 1 degree (working in the 0.2-10 keV energy band), dedicated to the rapid follow-up of the Gamma-Ray Bursts counterparts and to their precise localization (smaller than 2 arc minutes). In order to reduce the optics mass and to have an angular resolution of few arc minutes, a "lobster-Eye" configuration has been chosen. Using a numerical model of the MXT Point Spread Function (PSF) we simulated MXT observations of point sources in order to develop and test different localization algorithms to be implemented on board MXT. We included preliminary estimations of the instrumental and sky background. The algorithms on board have to be a combination of speed and precision (the brightest sources are expected to be localized at a precision better than 10 arc seconds in the MXT reference frame). We present the comparison between different methods such as barycentre, PSF fitting in one or two dimensions. The temporal performance of the algorithms is being tested using the X-ray afterglow data base of the XRT telescope on board the NASA Swift satellite.

High-speed peak matching algorithm for retention time alignment of gas chromatographic data for chemometric analysis.

PubMed

Johnson, Kevin J; Wright, Bob W; Jarman, Kristin H; Synovec, Robert E

2003-05-09

A rapid retention time alignment algorithm was developed as a preprocessing utility to be used prior to chemometric analysis of large datasets of diesel fuel profiles obtained using gas chromatography (GC). Retention time variation from chromatogram-to-chromatogram has been a significant impediment against the use of chemometric techniques in the analysis of chromatographic data due to the inability of current chemometric techniques to correctly model information that shifts from variable to variable within a dataset. The alignment algorithm developed is shown to increase the efficacy of pattern recognition methods applied to diesel fuel chromatograms by retaining chemical selectivity while reducing chromatogram-to-chromatogram retention time variations and to do so on a time scale that makes analysis of large sets of chromatographic data practical. Two sets of diesel fuel gas chromatograms were studied using the novel alignment algorithm followed by principal component analysis (PCA). In the first study, retention times for corresponding chromatographic peaks in 60 chromatograms varied by as much as 300 ms between chromatograms before alignment. In the second study of 42 chromatograms, the retention time shifting exhibited was on the order of 10 s between corresponding chromatographic peaks, and required a coarse retention time correction prior to alignment with the algorithm. In both cases, an increase in retention time precision afforded by the algorithm was clearly visible in plots of overlaid chromatograms before and then after applying the retention time alignment algorithm. Using the alignment algorithm, the standard deviation for corresponding peak retention times following alignment was 17 ms throughout a given chromatogram, corresponding to a relative standard deviation of 0.003% at an average retention time of 8 min. This level of retention time precision is a 5-fold improvement over the retention time precision initially provided by a state-of-the-art GC instrument equipped with electronic pressure control and was critical to the performance of the chemometric analysis. This increase in retention time precision does not come at the expense of chemical selectivity, since the PCA results suggest that essentially all of the chemical selectivity is preserved. Cluster resolution between dissimilar groups of diesel fuel chromatograms in a two-dimensional scores space generated with PCA is shown to substantially increase after alignment. The alignment method is robust against missing or extra peaks relative to a target chromatogram used in the alignment, and operates at high speed, requiring roughly 1 s of computation time per GC chromatogram.

Variable-Length Computerized Adaptive Testing Based on Cognitive Diagnosis Models

ERIC Educational Resources Information Center

Hsu, Chia-Ling; Wang, Wen-Chung; Chen, Shu-Ying

2013-01-01

Interest in developing computerized adaptive testing (CAT) under cognitive diagnosis models (CDMs) has increased recently. CAT algorithms that use a fixed-length termination rule frequently lead to different degrees of measurement precision for different examinees. Fixed precision, in which the examinees receive the same degree of measurement…

The String Stability of a Trajectory-Based Interval Management Algorithm in the Midterm Airspace

NASA Technical Reports Server (NTRS)

Swieringa, Kurt A.

2015-01-01

NASA's first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the terminal airspace; Controller Managed Spacing (CMS), which provides terminal controllers with decision support tools enabling precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain a precise spacing interval behind a target aircraft. As the percentage of IM equipped aircraft increases, controllers may provide IM clearances to sequences, or strings, of IM-equipped aircraft. It is important for these strings to maintain stable performance. This paper describes an analytic analysis of the string stability of the latest version of NASA's IM algorithm and a fast-time simulation designed to characterize the string performance of the IM algorithm. The analytic analysis showed that the spacing algorithm has stable poles, indicating that a spacing error perturbation will be reduced as a function of string position. The fast-time simulation investigated IM operations at two airports using constraints associated with the midterm airspace, including limited information of the target aircraft's intended speed profile and limited information of the wind forecast on the target aircraft's route. The results of the fast-time simulation demonstrated that the performance of the spacing algorithm is acceptable for strings of moderate length; however, there is some degradation in IM performance as a function of string position.

Analysis of Flexible Bars and Frames with Large Displacements of Nodes By Finite Element Method in the Form of Classical Mixed Method

NASA Astrophysics Data System (ADS)

Ignatyev, A. V.; Ignatyev, V. A.; Onischenko, E. V.

2017-11-01

This article is the continuation of the work made bt the authors on the development of the algorithms that implement the finite element method in the form of a classical mixed method for the analysis of geometrically nonlinear bar systems [1-3]. The paper describes an improved algorithm of the formation of the nonlinear governing equations system for flexible plane frames and bars with large displacements of nodes based on the finite element method in a mixed classical form and the use of the procedure of step-by-step loading. An example of the analysis is given.

A method of minimum volume simplex analysis constrained unmixing for hyperspectral image

NASA Astrophysics Data System (ADS)

Zou, Jinlin; Lan, Jinhui; Zeng, Yiliang; Wu, Hongtao

2017-07-01

The signal recorded by a low resolution hyperspectral remote sensor from a given pixel, letting alone the effects of the complex terrain, is a mixture of substances. To improve the accuracy of classification and sub-pixel object detection, hyperspectral unmixing(HU) is a frontier-line in remote sensing area. Unmixing algorithm based on geometric has become popular since the hyperspectral image possesses abundant spectral information and the mixed model is easy to understand. However, most of the algorithms are based on pure pixel assumption, and since the non-linear mixed model is complex, it is hard to obtain the optimal endmembers especially under a highly mixed spectral data. To provide a simple but accurate method, we propose a minimum volume simplex analysis constrained (MVSAC) unmixing algorithm. The proposed approach combines the algebraic constraints that are inherent to the convex minimum volume with abundance soft constraint. While considering abundance fraction, we can obtain the pure endmember set and abundance fraction correspondingly, and the final unmixing result is closer to reality and has better accuracy. We illustrate the performance of the proposed algorithm in unmixing simulated data and real hyperspectral data, and the result indicates that the proposed method can obtain the distinct signatures correctly without redundant endmember and yields much better performance than the pure pixel based algorithm.

Mixed raster content (MRC) model for compound image compression

NASA Astrophysics Data System (ADS)

de Queiroz, Ricardo L.; Buckley, Robert R.; Xu, Ming

1998-12-01

This paper will describe the Mixed Raster Content (MRC) method for compressing compound images, containing both binary test and continuous-tone images. A single compression algorithm that simultaneously meets the requirements for both text and image compression has been elusive. MRC takes a different approach. Rather than using a single algorithm, MRC uses a multi-layered imaging model for representing the results of multiple compression algorithms, including ones developed specifically for text and for images. As a result, MRC can combine the best of existing or new compression algorithms and offer different quality-compression ratio tradeoffs. The algorithms used by MRC set the lower bound on its compression performance. Compared to existing algorithms, MRC has some image-processing overhead to manage multiple algorithms and the imaging model. This paper will develop the rationale for the MRC approach by describing the multi-layered imaging model in light of a rate-distortion trade-off. Results will be presented comparing images compressed using MRC, JPEG and state-of-the-art wavelet algorithms such as SPIHT. MRC has been approved or proposed as an architectural model for several standards, including ITU Color Fax, IETF Internet Fax, and JPEG 2000.

Generalization of mixed multiscale finite element methods with applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, C S

Many science and engineering problems exhibit scale disparity and high contrast. The small scale features cannot be omitted in the physical models because they can affect the macroscopic behavior of the problems. However, resolving all the scales in these problems can be prohibitively expensive. As a consequence, some types of model reduction techniques are required to design efficient solution algorithms. For practical purpose, we are interested in mixed finite element problems as they produce solutions with certain conservative properties. Existing multiscale methods for such problems include the mixed multiscale finite element methods. We show that for complicated problems, the mixedmore » multiscale finite element methods may not be able to produce reliable approximations. This motivates the need of enrichment for coarse spaces. Two enrichment approaches are proposed, one is based on generalized multiscale finte element metthods (GMsFEM), while the other is based on spectral element-based algebraic multigrid (rAMGe). The former one, which is called mixed GMsFEM, is developed for both Darcy’s flow and linear elasticity. Application of the algorithm in two-phase flow simulations are demonstrated. For linear elasticity, the algorithm is subtly modified due to the symmetry requirement of the stress tensor. The latter enrichment approach is based on rAMGe. The algorithm differs from GMsFEM in that both of the velocity and pressure spaces are coarsened. Due the multigrid nature of the algorithm, recursive application is available, which results in an efficient multilevel construction of the coarse spaces. Stability, convergence analysis, and exhaustive numerical experiments are carried out to validate the proposed enrichment approaches. iii« less

Hardron production and neutrino beams

NASA Astrophysics Data System (ADS)

Guglielmi, A.

2006-11-01

The precise measurements of the neutrino mixing parameters in the oscillation experiments at accelerators require new high-intensity and high-purity neutrino beams. Ancillary hadron-production measurements are then needed as inputs to precise calculation of neutrino beams and of atmospheric neutrino fluxes.

A novel fast phase correlation algorithm for peak wavelength detection of Fiber Bragg Grating sensors.

PubMed

Lamberti, A; Vanlanduit, S; De Pauw, B; Berghmans, F

2014-03-24

Fiber Bragg Gratings (FBGs) can be used as sensors for strain, temperature and pressure measurements. For this purpose, the ability to determine the Bragg peak wavelength with adequate wavelength resolution and accuracy is essential. However, conventional peak detection techniques, such as the maximum detection algorithm, can yield inaccurate and imprecise results, especially when the Signal to Noise Ratio (SNR) and the wavelength resolution are poor. Other techniques, such as the cross-correlation demodulation algorithm are more precise and accurate but require a considerable higher computational effort. To overcome these problems, we developed a novel fast phase correlation (FPC) peak detection algorithm, which computes the wavelength shift in the reflected spectrum of a FBG sensor. This paper analyzes the performance of the FPC algorithm for different values of the SNR and wavelength resolution. Using simulations and experiments, we compared the FPC with the maximum detection and cross-correlation algorithms. The FPC method demonstrated a detection precision and accuracy comparable with those of cross-correlation demodulation and considerably higher than those obtained with the maximum detection technique. Additionally, FPC showed to be about 50 times faster than the cross-correlation. It is therefore a promising tool for future implementation in real-time systems or in embedded hardware intended for FBG sensor interrogation.

Real-Time Gait Event Detection Based on Kinematic Data Coupled to a Biomechanical Model.

PubMed

Lambrecht, Stefan; Harutyunyan, Anna; Tanghe, Kevin; Afschrift, Maarten; De Schutter, Joris; Jonkers, Ilse

2017-03-24

Real-time detection of multiple stance events, more specifically initial contact (IC), foot flat (FF), heel off (HO), and toe off (TO), could greatly benefit neurorobotic (NR) and neuroprosthetic (NP) control. Three real-time threshold-based algorithms have been developed, detecting the aforementioned events based on kinematic data in combination with a biomechanical model. Data from seven subjects walking at three speeds on an instrumented treadmill were used to validate the presented algorithms, accumulating to a total of 558 steps. The reference for the gait events was obtained using marker and force plate data. All algorithms had excellent precision and no false positives were observed. Timing delays of the presented algorithms were similar to current state-of-the-art algorithms for the detection of IC and TO, whereas smaller delays were achieved for the detection of FF. Our results indicate that, based on their high precision and low delays, these algorithms can be used for the control of an NR/NP, with the exception of the HO event. Kinematic data is used in most NR/NP control schemes and is thus available at no additional cost, resulting in a minimal computational burden. The presented methods can also be applied for screening pathological gait or gait analysis in general in/outside of the laboratory.

Evaluating an image-fusion algorithm with synthetic-image-generation tools

NASA Astrophysics Data System (ADS)

Gross, Harry N.; Schott, John R.

1996-06-01

An algorithm that combines spectral mixing and nonlinear optimization is used to fuse multiresolution images. Image fusion merges images of different spatial and spectral resolutions to create a high spatial resolution multispectral combination. High spectral resolution allows identification of materials in the scene, while high spatial resolution locates those materials. In this algorithm, conventional spectral mixing estimates the percentage of each material (called endmembers) within each low resolution pixel. Three spectral mixing models are compared; unconstrained, partially constrained, and fully constrained. In the partially constrained application, the endmember fractions are required to sum to one. In the fully constrained application, all fractions are additionally required to lie between zero and one. While negative fractions seem inappropriate, they can arise from random spectral realizations of the materials. In the second part of the algorithm, the low resolution fractions are used as inputs to a constrained nonlinear optimization that calculates the endmember fractions for the high resolution pixels. The constraints mirror the low resolution constraints and maintain consistency with the low resolution fraction results. The algorithm can use one or more higher resolution sharpening images to locate the endmembers to high spatial accuracy. The algorithm was evaluated with synthetic image generation (SIG) tools. A SIG developed image can be used to control the various error sources that are likely to impair the algorithm performance. These error sources include atmospheric effects, mismodeled spectral endmembers, and variability in topography and illumination. By controlling the introduction of these errors, the robustness of the algorithm can be studied and improved upon. The motivation for this research is to take advantage of the next generation of multi/hyperspectral sensors. Although the hyperspectral images will be of modest to low resolution, fusing them with high resolution sharpening images will produce a higher spatial resolution land cover or material map.

The psychopharmacology algorithm project at the Harvard South Shore Program: an algorithm for acute mania.

PubMed

Mohammad, Othman; Osser, David N

2014-01-01

This new algorithm for the pharmacotherapy of acute mania was developed by the Psychopharmacology Algorithm Project at the Harvard South Shore Program. The authors conducted a literature search in PubMed and reviewed key studies, other algorithms and guidelines, and their references. Treatments were prioritized considering three main considerations: (1) effectiveness in treating the current episode, (2) preventing potential relapses to depression, and (3) minimizing side effects over the short and long term. The algorithm presupposes that clinicians have made an accurate diagnosis, decided how to manage contributing medical causes (including substance misuse), discontinued antidepressants, and considered the patient's childbearing potential. We propose different algorithms for mixed and nonmixed mania. Patients with mixed mania may be treated first with a second-generation antipsychotic, of which the first choice is quetiapine because of its greater efficacy for depressive symptoms and episodes in bipolar disorder. Valproate and then either lithium or carbamazepine may be added. For nonmixed mania, lithium is the first-line recommendation. A second-generation antipsychotic can be added. Again, quetiapine is favored, but if quetiapine is unacceptable, risperidone is the next choice. Olanzapine is not considered a first-line treatment due to its long-term side effects, but it could be second-line. If the patient, whether mixed or nonmixed, is still refractory to the above medications, then depending on what has already been tried, consider carbamazepine, haloperidol, olanzapine, risperidone, and valproate first tier; aripiprazole, asenapine, and ziprasidone second tier; and clozapine third tier (because of its weaker evidence base and greater side effects). Electroconvulsive therapy may be considered at any point in the algorithm if the patient has a history of positive response or is intolerant of medications.

Automatic Syllabification in English: A Comparison of Different Algorithms

ERIC Educational Resources Information Center

Marchand, Yannick; Adsett, Connie R.; Damper, Robert I.

2009-01-01

Automatic syllabification of words is challenging, not least because the syllable is not easy to define precisely. Consequently, no accepted standard algorithm for automatic syllabification exists. There are two broad approaches: rule-based and data-driven. The rule-based method effectively embodies some theoretical position regarding the…

Hyper-spectral image compression algorithm based on mixing transform of wave band grouping to eliminate redundancy

NASA Astrophysics Data System (ADS)

Xie, ChengJun; Xu, Lin

2008-03-01

This paper presents an algorithm based on mixing transform of wave band grouping to eliminate spectral redundancy, the algorithm adapts to the relativity difference between different frequency spectrum images, and still it works well when the band number is not the power of 2. Using non-boundary extension CDF(2,2)DWT and subtraction mixing transform to eliminate spectral redundancy, employing CDF(2,2)DWT to eliminate spatial redundancy and SPIHT+CABAC for compression coding, the experiment shows that a satisfied lossless compression result can be achieved. Using hyper-spectral image Canal of American JPL laboratory as the data set for lossless compression test, when the band number is not the power of 2, lossless compression result of this compression algorithm is much better than the results acquired by JPEG-LS, WinZip, ARJ, DPCM, the research achievements of a research team of Chinese Academy of Sciences, Minimum Spanning Tree and Near Minimum Spanning Tree, on the average the compression ratio of this algorithm exceeds the above algorithms by 41%,37%,35%,29%,16%,10%,8% respectively; when the band number is the power of 2, for 128 frames of the image Canal, taking 8, 16 and 32 respectively as the number of one group for groupings based on different numbers, considering factors like compression storage complexity, the type of wave band and the compression effect, we suggest using 8 as the number of bands included in one group to achieve a better compression effect. The algorithm of this paper has priority in operation speed and hardware realization convenience.

A novel material detection algorithm based on 2D GMM-based power density function and image detail addition scheme in dual energy X-ray images.

PubMed

Pourghassem, Hossein

2012-01-01

Material detection is a vital need in dual energy X-ray luggage inspection systems at security of airport and strategic places. In this paper, a novel material detection algorithm based on statistical trainable models using 2-Dimensional power density function (PDF) of three material categories in dual energy X-ray images is proposed. In this algorithm, the PDF of each material category as a statistical model is estimated from transmission measurement values of low and high energy X-ray images by Gaussian Mixture Models (GMM). Material label of each pixel of object is determined based on dependency probability of its transmission measurement values in the low and high energy to PDF of three material categories (metallic, organic and mixed materials). The performance of material detection algorithm is improved by a maximum voting scheme in a neighborhood of image as a post-processing stage. Using two background removing and denoising stages, high and low energy X-ray images are enhanced as a pre-processing procedure. For improving the discrimination capability of the proposed material detection algorithm, the details of the low and high energy X-ray images are added to constructed color image which includes three colors (orange, blue and green) for representing the organic, metallic and mixed materials. The proposed algorithm is evaluated on real images that had been captured from a commercial dual energy X-ray luggage inspection system. The obtained results show that the proposed algorithm is effective and operative in detection of the metallic, organic and mixed materials with acceptable accuracy.

Fast mix table construction for material discretization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, S. R.

2013-07-01

An effective hybrid Monte Carlo-deterministic implementation typically requires the approximation of a continuous geometry description with a discretized piecewise-constant material field. The inherent geometry discretization error can be reduced somewhat by using material mixing, where multiple materials inside a discrete mesh voxel are homogenized. Material mixing requires the construction of a 'mix table,' which stores the volume fractions in every mixture so that multiple voxels with similar compositions can reference the same mixture. Mix table construction is a potentially expensive serial operation for large problems with many materials and voxels. We formulate an efficient algorithm to construct a sparse mixmore » table in O(number of voxels x log number of mixtures) time. The new algorithm is implemented in ADVANTG and used to discretize continuous geometries onto a structured Cartesian grid. When applied to an end-of-life MCNP model of the High Flux Isotope Reactor with 270 distinct materials, the new method improves the material mixing time by a factor of 100 compared to a naive mix table implementation. (authors)« less

Combination of GPS and GLONASS IN PPP algorithms and its effect on site coordinates determination

NASA Astrophysics Data System (ADS)

Hefty, J.; Gerhatova, L.; Burgan, J.

2011-10-01

Precise Point Positioning (PPP) approach using the un-differenced code and phase GPS observations, precise orbits and satellite clocks is an important alternative to the analyses based on double differences. We examine the extension of the PPP method by introducing the GLONASS satellites into the processing algorithms. The procedures are demonstrated on the software package ABSOLUTE developed at the Slovak University of Technology. Partial results, like ambiguities and receiver clocks obtained from separate solutions of the two GNSS are mutually compared. Finally, the coordinate time series from combination of GPS and GLONASS observations are compared with GPS-only solutions.

StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images.

PubMed

De Backer, A; van den Bos, K H W; Van den Broek, W; Sijbers, J; Van Aert, S

2016-12-01

An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, has been investigated. The highest attainable precision is reached even for low dose images. Furthermore, the advantages of the model-based approach taking into account overlap between neighbouring columns are highlighted. This is done for the estimation of the distance between two neighbouring columns as a function of their distance and for the estimation of the scattering cross-section which is compared to the integrated intensity from a Voronoi cell. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license. Copyright © 2016 Elsevier B.V. All rights reserved.

Learning-based computing techniques in geoid modeling for precise height transformation

NASA Astrophysics Data System (ADS)

Erol, B.; Erol, S.

2013-03-01

Precise determination of local geoid is of particular importance for establishing height control in geodetic GNSS applications, since the classical leveling technique is too laborious. A geoid model can be accurately obtained employing properly distributed benchmarks having GNSS and leveling observations using an appropriate computing algorithm. Besides the classical multivariable polynomial regression equations (MPRE), this study attempts an evaluation of learning based computing algorithms: artificial neural networks (ANNs), adaptive network-based fuzzy inference system (ANFIS) and especially the wavelet neural networks (WNNs) approach in geoid surface approximation. These algorithms were developed parallel to advances in computer technologies and recently have been used for solving complex nonlinear problems of many applications. However, they are rather new in dealing with precise modeling problem of the Earth gravity field. In the scope of the study, these methods were applied to Istanbul GPS Triangulation Network data. The performances of the methods were assessed considering the validation results of the geoid models at the observation points. In conclusion the ANFIS and WNN revealed higher prediction accuracies compared to ANN and MPRE methods. Beside the prediction capabilities, these methods were also compared and discussed from the practical point of view in conclusions.

Piezoelectric self-sensing actuator for active vibration control of motorized spindle based on adaptive signal separation

NASA Astrophysics Data System (ADS)

He, Ye; Chen, Xiaoan; Liu, Zhi; Qin, Yi

2018-06-01

The motorized spindle is the core component of CNC machine tools, and the vibration of it reduces the machining precision and service life of the machine tools. Owing to the fast response, large output force, and displacement of the piezoelectric stack, it is often used as the actuator in the active vibration control of the spindle. A piezoelectric self-sensing actuator (SSA) can reduce the cost of the active vibration control system and simplify the structure by eliminating the use of a sensor, because a SSA can have both actuating and sensing functions at the same time. The signal separation method of a SSA based on a bridge circuit is widely applied because of its simple principle and easy implementation. However, it is difficult to maintain dynamic balance of the circuit. Prior research has used adaptive algorithm to balance of the bridge circuit on the flexible beam dynamically, but those algorithms need no correlation between sensing and control voltage, which limit the applications of SSA in the vibration control of the rotor-bearing system. Here, the electromechanical coupling model of the piezoelectric stack is established, followed by establishment of the dynamic model of the spindle system. Next, a new adaptive signal separation method based on the bridge circuit is proposed, which can separate relative small sensing voltage from related mixed voltage adaptively. The experimental results show that when the self-sensing signal obtained from the proposed method is used as a displacement signal, the vibration of the motorized spindle can be suppressed effectively through a linear quadratic Gaussian (LQG) algorithm.

Incompressible SPH (ISPH) with fast Poisson solver on a GPU

NASA Astrophysics Data System (ADS)

Chow, Alex D.; Rogers, Benedict D.; Lind, Steven J.; Stansby, Peter K.

2018-05-01

This paper presents a fast incompressible SPH (ISPH) solver implemented to run entirely on a graphics processing unit (GPU) capable of simulating several millions of particles in three dimensions on a single GPU. The ISPH algorithm is implemented by converting the highly optimised open-source weakly-compressible SPH (WCSPH) code DualSPHysics to run ISPH on the GPU, combining it with the open-source linear algebra library ViennaCL for fast solutions of the pressure Poisson equation (PPE). Several challenges are addressed with this research: constructing a PPE matrix every timestep on the GPU for moving particles, optimising the limited GPU memory, and exploiting fast matrix solvers. The ISPH pressure projection algorithm is implemented as 4 separate stages, each with a particle sweep, including an algorithm for the population of the PPE matrix suitable for the GPU, and mixed precision storage methods. An accurate and robust ISPH boundary condition ideal for parallel processing is also established by adapting an existing WCSPH boundary condition for ISPH. A variety of validation cases are presented: an impulsively started plate, incompressible flow around a moving square in a box, and dambreaks (2-D and 3-D) which demonstrate the accuracy, flexibility, and speed of the methodology. Fragmentation of the free surface is shown to influence the performance of matrix preconditioners and therefore the PPE matrix solution time. The Jacobi preconditioner demonstrates robustness and reliability in the presence of fragmented flows. For a dambreak simulation, GPU speed ups demonstrate up to 10-18 times and 1.1-4.5 times compared to single-threaded and 16-threaded CPU run times respectively.

Accuracy of both virtual and printed 3-dimensional models for volumetric measurement of alveolar clefts before grafting with alveolar bone compared with a validated algorithm: a preliminary investigation.

PubMed

Kasaven, C P; McIntyre, G T; Mossey, P A

2017-01-01

Our objective was to assess the accuracy of virtual and printed 3-dimensional models derived from cone-beam computed tomographic (CT) scans to measure the volume of alveolar clefts before bone grafting. Fifteen subjects with unilateral cleft lip and palate had i-CAT cone-beam CT scans recorded at 0.2mm voxel and sectioned transversely into slices 0.2mm thick using i-CAT Vision. Volumes of alveolar clefts were calculated using first a validated algorithm; secondly, commercially-available virtual 3-dimensional model software; and finally 3-dimensional printed models, which were scanned with microCT and analysed using 3-dimensional software. For inter-observer reliability, a two-way mixed model intraclass correlation coefficient (ICC) was used to evaluate the reproducibility of identification of the cranial and caudal limits of the clefts among three observers. We used a Friedman test to assess the significance of differences among the methods, and probabilities of less than 0.05 were accepted as significant. Inter-observer reliability was almost perfect (ICC=0.987). There were no significant differences among the three methods. Virtual and printed 3-dimensional models were as precise as the validated computer algorithm in the calculation of volumes of the alveolar cleft before bone grafting, but virtual 3-dimensional models were the most accurate with the smallest 95% CI and, subject to further investigation, could be a useful adjunct in clinical practice. Copyright © 2016 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Parametric geometric model and hydrodynamic shape optimization of a flying-wing structure underwater glider

NASA Astrophysics Data System (ADS)

Wang, Zhen-yu; Yu, Jian-cheng; Zhang, Ai-qun; Wang, Ya-xing; Zhao, Wen-tao

2017-12-01

Combining high precision numerical analysis methods with optimization algorithms to make a systematic exploration of a design space has become an important topic in the modern design methods. During the design process of an underwater glider's flying-wing structure, a surrogate model is introduced to decrease the computation time for a high precision analysis. By these means, the contradiction between precision and efficiency is solved effectively. Based on the parametric geometry modeling, mesh generation and computational fluid dynamics analysis, a surrogate model is constructed by adopting the design of experiment (DOE) theory to solve the multi-objects design optimization problem of the underwater glider. The procedure of a surrogate model construction is presented, and the Gaussian kernel function is specifically discussed. The Particle Swarm Optimization (PSO) algorithm is applied to hydrodynamic design optimization. The hydrodynamic performance of the optimized flying-wing structure underwater glider increases by 9.1%.

The fuzzy algorithm in the die casting mould for the application of multi-channel temperature control

NASA Astrophysics Data System (ADS)

Sun, Jin-gen; Chen, Yi; Zhang, Jia-nan

2017-01-01

Mould manufacturing is one of the most basic elements in the production chain of China. The mould manufacturing technology has become an important symbol to measure the level of a country's manufacturing industry. The die-casting mould multichannel intelligent temperature control method is studied by cooling water circulation, which uses fuzzy control to realize, aiming at solving the shortcomings of slow speed and big energy consumption during the cooling process of current die-casting mould. At present, the traditional PID control method is used to control the temperature, but it is difficult to ensure the control precision. While , the fuzzy algorithm is used to realize precise control of mould temperature in cooling process. The design is simple, fast response, strong anti-interference ability and good robustness. Simulation results show that the control method is completely feasible, which has higher control precision.

Phylogenetic search through partial tree mixing

PubMed Central

2012-01-01

Background Recent advances in sequencing technology have created large data sets upon which phylogenetic inference can be performed. Current research is limited by the prohibitive time necessary to perform tree search on a reasonable number of individuals. This research develops new phylogenetic algorithms that can operate on tens of thousands of species in a reasonable amount of time through several innovative search techniques. Results When compared to popular phylogenetic search algorithms, better trees are found much more quickly for large data sets. These algorithms are incorporated in the PSODA application available at http://dna.cs.byu.edu/psoda Conclusions The use of Partial Tree Mixing in a partition based tree space allows the algorithm to quickly converge on near optimal tree regions. These regions can then be searched in a methodical way to determine the overall optimal phylogenetic solution. PMID:23320449

Electronic Health Record Phenotypes for Precision Medicine: Perspectives and Caveats From Treatment of Breast Cancer at a Single Institution

PubMed Central

Liu, Hongfang; Maxwell, Kara N.; Pathak, Jyotishman; Zhang, Rui

2018-01-01

Abstract Precision medicine is at the forefront of biomedical research. Cancer registries provide rich perspectives and electronic health records (EHRs) are commonly utilized to gather additional clinical data elements needed for translational research. However, manual annotation is resource‐intense and not readily scalable. Informatics‐based phenotyping presents an ideal solution, but perspectives obtained can be impacted by both data source and algorithm selection. We derived breast cancer (BC) receptor status phenotypes from structured and unstructured EHR data using rule‐based algorithms, including natural language processing (NLP). Overall, the use of NLP increased BC receptor status coverage by 39.2% from 69.1% with structured medication information alone. Using all available EHR data, estrogen receptor‐positive BC cases were ascertained with high precision (P = 0.976) and recall (R = 0.987) compared with gold standard chart‐reviewed patients. However, status negation (R = 0.591) decreased 40.2% when relying on structured medications alone. Using multiple EHR data types (and thorough understanding of the perspectives offered) are necessary to derive robust EHR‐based precision medicine phenotypes. PMID:29084368

Efficient Computational Prototyping of Mixed Technology Microfluidic Components and Systems

DTIC Science & Technology

2002-08-01

AFRL-IF-RS-TR-2002-190 Final Technical Report August 2002 EFFICIENT COMPUTATIONAL PROTOTYPING OF MIXED TECHNOLOGY MICROFLUIDIC...SUBTITLE EFFICIENT COMPUTATIONAL PROTOTYPING OF MIXED TECHNOLOGY MICROFLUIDIC COMPONENTS AND SYSTEMS 6. AUTHOR(S) Narayan R. Aluru, Jacob White...Aided Design (CAD) tools for microfluidic components and systems were developed in this effort. Innovative numerical methods and algorithms for mixed

Using frequency analysis to improve the precision of human body posture algorithms based on Kalman filters.

PubMed

Olivares, Alberto; Górriz, J M; Ramírez, J; Olivares, G

2016-05-01

With the advent of miniaturized inertial sensors many systems have been developed within the last decade to study and analyze human motion and posture, specially in the medical field. Data measured by the sensors are usually processed by algorithms based on Kalman Filters in order to estimate the orientation of the body parts under study. These filters traditionally include fixed parameters, such as the process and observation noise variances, whose value has large influence in the overall performance. It has been demonstrated that the optimal value of these parameters differs considerably for different motion intensities. Therefore, in this work, we show that, by applying frequency analysis to determine motion intensity, and varying the formerly fixed parameters accordingly, the overall precision of orientation estimation algorithms can be improved, therefore providing physicians with reliable objective data they can use in their daily practice. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Nonlinear, Six-Degree of Freedom Precision Formation Control Algorithm, Based on Restricted Three Body Dynamics

NASA Technical Reports Server (NTRS)

Bauer, Frank (Technical Monitor); Luquette, Richard J.; Sanner, Robert M.

2003-01-01

Precision Formation Flying is an enabling technology for a variety of proposed space-based observatories, including the Micro-Arcsecond X-ray Imaging Mission (MAXIM), the associated MAXIM pathfinder mission, and the Stellar Imager. An essential element of the technology is the control algorithm. This paper discusses the development of a nonlinear, six-degree of freedom (6DOF) control algorithm for maintaining the relative position and attitude of a spacecraft within a formation. The translation dynamics are based on the equations of motion for the restricted three body problem. The control law guarantees the tracking error convergences to zero, based on a Lyapunov analysis. The simulation, modelled after the MAXIM Pathfinder mission, maintains the relative position and attitude of a Follower spacecraft with respect to a Leader spacecraft, stationed near the L2 libration point in the Sun-Earth system.

LS-CAP: an algorithm for identifying cytogenetic aberrations in hepatocellular carcinoma using microarray data.

PubMed

He, Xianmin; Wei, Qing; Sun, Meiqian; Fu, Xuping; Fan, Sichang; Li, Yao

2006-05-01

Biological techniques such as Array-Comparative genomic hybridization (CGH), fluorescent in situ hybridization (FISH) and affymetrix single nucleotide pleomorphism (SNP) array have been used to detect cytogenetic aberrations. However, on genomic scale, these techniques are labor intensive and time consuming. Comparative genomic microarray analysis (CGMA) has been used to identify cytogenetic changes in hepatocellular carcinoma (HCC) using gene expression microarray data. However, CGMA algorithm can not give precise localization of aberrations, fails to identify small cytogenetic changes, and exhibits false negatives and positives. Locally un-weighted smoothing cytogenetic aberrations prediction (LS-CAP) based on local smoothing and binomial distribution can be expected to address these problems. LS-CAP algorithm was built and used on HCC microarray profiles. Eighteen cytogenetic abnormalities were identified, among them 5 were reported previously, and 12 were proven by CGH studies. LS-CAP effectively reduced the false negatives and positives, and precisely located small fragments with cytogenetic aberrations.

Independent component analysis algorithm FPGA design to perform real-time blind source separation

NASA Astrophysics Data System (ADS)

Meyer-Baese, Uwe; Odom, Crispin; Botella, Guillermo; Meyer-Baese, Anke

2015-05-01

The conditions that arise in the Cocktail Party Problem prevail across many fields creating a need for of Blind Source Separation. The need for BSS has become prevalent in several fields of work. These fields include array processing, communications, medical signal processing, and speech processing, wireless communication, audio, acoustics and biomedical engineering. The concept of the cocktail party problem and BSS led to the development of Independent Component Analysis (ICA) algorithms. ICA proves useful for applications needing real time signal processing. The goal of this research was to perform an extensive study on ability and efficiency of Independent Component Analysis algorithms to perform blind source separation on mixed signals in software and implementation in hardware with a Field Programmable Gate Array (FPGA). The Algebraic ICA (A-ICA), Fast ICA, and Equivariant Adaptive Separation via Independence (EASI) ICA were examined and compared. The best algorithm required the least complexity and fewest resources while effectively separating mixed sources. The best algorithm was the EASI algorithm. The EASI ICA was implemented on hardware with Field Programmable Gate Arrays (FPGA) to perform and analyze its performance in real time.

A numerical similarity approach for using retired Current Procedural Terminology (CPT) codes for electronic phenotyping in the Scalable Collaborative Infrastructure for a Learning Health System (SCILHS).

PubMed

Klann, Jeffrey G; Phillips, Lori C; Turchin, Alexander; Weiler, Sarah; Mandl, Kenneth D; Murphy, Shawn N

2015-12-11

Interoperable phenotyping algorithms, needed to identify patient cohorts meeting eligibility criteria for observational studies or clinical trials, require medical data in a consistent structured, coded format. Data heterogeneity limits such algorithms' applicability. Existing approaches are often: not widely interoperable; or, have low sensitivity due to reliance on the lowest common denominator (ICD-9 diagnoses). In the Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS) we endeavor to use the widely-available Current Procedural Terminology (CPT) procedure codes with ICD-9. Unfortunately, CPT changes drastically year-to-year - codes are retired/replaced. Longitudinal analysis requires grouping retired and current codes. BioPortal provides a navigable CPT hierarchy, which we imported into the Informatics for Integrating Biology and the Bedside (i2b2) data warehouse and analytics platform. However, this hierarchy does not include retired codes. We compared BioPortal's 2014AA CPT hierarchy with Partners Healthcare's SCILHS datamart, comprising three-million patients' data over 15 years. 573 CPT codes were not present in 2014AA (6.5 million occurrences). No existing terminology provided hierarchical linkages for these missing codes, so we developed a method that automatically places missing codes in the most specific "grouper" category, using the numerical similarity of CPT codes. Two informaticians reviewed the results. We incorporated the final table into our i2b2 SCILHS/PCORnet ontology, deployed it at seven sites, and performed a gap analysis and an evaluation against several phenotyping algorithms. The reviewers found the method placed the code correctly with 97 % precision when considering only miscategorizations ("correctness precision") and 52 % precision using a gold-standard of optimal placement ("optimality precision"). High correctness precision meant that codes were placed in a reasonable hierarchal position that a reviewer can quickly validate. Lower optimality precision meant that codes were not often placed in the optimal hierarchical subfolder. The seven sites encountered few occurrences of codes outside our ontology, 93 % of which comprised just four codes. Our hierarchical approach correctly grouped retired and non-retired codes in most cases and extended the temporal reach of several important phenotyping algorithms. We developed a simple, easily-validated, automated method to place retired CPT codes into the BioPortal CPT hierarchy. This complements existing hierarchical terminologies, which do not include retired codes. The approach's utility is confirmed by the high correctness precision and successful grouping of retired with non-retired codes.

Measuring Disorientation Based on the Needleman-Wunsch Algorithm

ERIC Educational Resources Information Center

Güyer, Tolga; Atasoy, Bilal; Somyürek, Sibel

2015-01-01

This study offers a new method to measure navigation disorientation in web based systems which is powerful learning medium for distance and open education. The Needleman-Wunsch algorithm is used to measure disorientation in a more precise manner. The process combines theoretical and applied knowledge from two previously distinct research areas,…

End-point detection in potentiometric titration by continuous wavelet transform.

PubMed

Jakubowska, Małgorzata; Baś, Bogusław; Kubiak, Władysław W

2009-10-15

The aim of this work was construction of the new wavelet function and verification that a continuous wavelet transform with a specially defined dedicated mother wavelet is a useful tool for precise detection of end-point in a potentiometric titration. The proposed algorithm does not require any initial information about the nature or the type of analyte and/or the shape of the titration curve. The signal imperfection, as well as random noise or spikes has no influence on the operation of the procedure. The optimization of the new algorithm was done using simulated curves and next experimental data were considered. In the case of well-shaped and noise-free titration data, the proposed method gives the same accuracy and precision as commonly used algorithms. But, in the case of noisy or badly shaped curves, the presented approach works good (relative error mainly below 2% and coefficients of variability below 5%) while traditional procedures fail. Therefore, the proposed algorithm may be useful in interpretation of the experimental data and also in automation of the typical titration analysis, specially in the case when random noise interfere with analytical signal.

Assessment of Gamma-Ray Spectra Analysis Method Utilizing the Fireworks Algorithm for various Error Measures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

2018-01-01

Significant role in enhancing nuclear nonproliferation plays the analysis of obtained data and the inference of the presence or not of special nuclear materials in them. Among various types of measurements, gamma-ray spectra is the widest used type of data utilized for analysis in nonproliferation. In this chapter, a method that employs the fireworks algorithm (FWA) for analyzing gamma-ray spectra aiming at detecting gamma signatures is presented. In particular FWA is utilized to fit a set of known signatures to a measured spectrum by optimizing an objective function, with non-zero coefficients expressing the detected signatures. FWA is tested on amore » set of experimentally obtained measurements and various objective functions -MSE, RMSE, Theil-2, MAE, MAPE, MAP- with results exhibiting its potential in providing high accuracy and high precision of detected signatures. Furthermore, FWA is benchmarked against genetic algorithms, and multiple linear regression with results exhibiting its superiority over the rest tested algorithms with respect to precision for MAE, MAPE and MAP measures.« less

Metaphor Identification in Large Texts Corpora

PubMed Central

Neuman, Yair; Assaf, Dan; Cohen, Yohai; Last, Mark; Argamon, Shlomo; Howard, Newton; Frieder, Ophir

2013-01-01

Identifying metaphorical language-use (e.g., sweet child) is one of the challenges facing natural language processing. This paper describes three novel algorithms for automatic metaphor identification. The algorithms are variations of the same core algorithm. We evaluate the algorithms on two corpora of Reuters and the New York Times articles. The paper presents the most comprehensive study of metaphor identification in terms of scope of metaphorical phrases and annotated corpora size. Algorithms’ performance in identifying linguistic phrases as metaphorical or literal has been compared to human judgment. Overall, the algorithms outperform the state-of-the-art algorithm with 71% precision and 27% averaged improvement in prediction over the base-rate of metaphors in the corpus. PMID:23658625

Research on wind field algorithm of wind lidar based on BP neural network and grey prediction

NASA Astrophysics Data System (ADS)

Chen, Yong; Chen, Chun-Li; Luo, Xiong; Zhang, Yan; Yang, Ze-hou; Zhou, Jie; Shi, Xiao-ding; Wang, Lei

2018-01-01

This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.

NASA Tech Briefs, December 2004

NASA Technical Reports Server (NTRS)

2004-01-01

opics include: High-Rate Digital Receiver Board; Signal Design for Improved Ranging Among Multiple Transceivers; Automated Analysis, Classification, and Display of Waveforms; Fast-Acquisition/Weak-Signal-Tracking GPS Receiver for HEO; Format for Interchange and Display of 3D Terrain Data; Program Analyzes Radar Altimeter Data; Indoor Navigation using Direction Sensor and Beacons; Software Assists in Responding to Anomalous Conditions; Software for Autonomous Spacecraft Maneuvers; WinPlot; Software for Automated Testing of Mission-Control Displays; Nanocarpets for Trapping Microscopic Particles; Precious-Metal Salt Coatings for Detecting Hydrazines; Amplifying Electrochemical Indicators; Better End-Cap Processing for Oxidation-Resistant Polyimides; Carbon-Fiber Brush Heat Exchangers; Solar-Powered Airplane with Cameras and WLAN; A Resonator for Low-Threshold Frequency Conversion; Masked Proportional Routing; Algorithm Determines Wind Speed and Direction from Venturi-Sensor Data; Feature-Identification and Data-Compression Software; Alternative Attitude Commanding and Control for Precise Spacecraft Landing; Inspecting Friction Stir Welding using Electromagnetic Probes; and Helicity in Supercritical O2/H2 and C7H16/N2 Mixing Layers.

Parallelized implicit propagators for the finite-difference Schrödinger equation

NASA Astrophysics Data System (ADS)

Parker, Jonathan; Taylor, K. T.

1995-08-01

We describe the application of block Gauss-Seidel and block Jacobi iterative methods to the design of implicit propagators for finite-difference models of the time-dependent Schrödinger equation. The block-wise iterative methods discussed here are mixed direct-iterative methods for solving simultaneous equations, in the sense that direct methods (e.g. LU decomposition) are used to invert certain block sub-matrices, and iterative methods are used to complete the solution. We describe parallel variants of the basic algorithm that are well suited to the medium- to coarse-grained parallelism of work-station clusters, and MIMD supercomputers, and we show that under a wide range of conditions, fine-grained parallelism of the computation can be achieved. Numerical tests are conducted on a typical one-electron atom Hamiltonian. The methods converge robustly to machine precision (15 significant figures), in some cases in as few as 6 or 7 iterations. The rate of convergence is nearly independent of the finite-difference grid-point separations.

Artificial neural network modelling of a large-scale wastewater treatment plant operation.

PubMed

Güçlü, Dünyamin; Dursun, Sükrü

2010-11-01

Artificial Neural Networks (ANNs), a method of artificial intelligence method, provide effective predictive models for complex processes. Three independent ANN models trained with back-propagation algorithm were developed to predict effluent chemical oxygen demand (COD), suspended solids (SS) and aeration tank mixed liquor suspended solids (MLSS) concentrations of the Ankara central wastewater treatment plant. The appropriate architecture of ANN models was determined through several steps of training and testing of the models. ANN models yielded satisfactory predictions. Results of the root mean square error, mean absolute error and mean absolute percentage error were 3.23, 2.41 mg/L and 5.03% for COD; 1.59, 1.21 mg/L and 17.10% for SS; 52.51, 44.91 mg/L and 3.77% for MLSS, respectively, indicating that the developed model could be efficiently used. The results overall also confirm that ANN modelling approach may have a great implementation potential for simulation, precise performance prediction and process control of wastewater treatment plants.

Accelerating adaptive inverse distance weighting interpolation algorithm on a graphics processing unit

PubMed Central

Xu, Liangliang; Xu, Nengxiong

2017-01-01

This paper focuses on designing and implementing parallel adaptive inverse distance weighting (AIDW) interpolation algorithms by using the graphics processing unit (GPU). The AIDW is an improved version of the standard IDW, which can adaptively determine the power parameter according to the data points’ spatial distribution pattern and achieve more accurate predictions than those predicted by IDW. In this paper, we first present two versions of the GPU-accelerated AIDW, i.e. the naive version without profiting from the shared memory and the tiled version taking advantage of the shared memory. We also implement the naive version and the tiled version using two data layouts, structure of arrays and array of aligned structures, on both single and double precision. We then evaluate the performance of parallel AIDW by comparing it with its corresponding serial algorithm on three different machines equipped with the GPUs GT730M, M5000 and K40c. The experimental results indicate that: (i) there is no significant difference in the computational efficiency when different data layouts are employed; (ii) the tiled version is always slightly faster than the naive version; and (iii) on single precision the achieved speed-up can be up to 763 (on the GPU M5000), while on double precision the obtained highest speed-up is 197 (on the GPU K40c). To benefit the community, all source code and testing data related to the presented parallel AIDW algorithm are publicly available. PMID:28989754

Accelerating adaptive inverse distance weighting interpolation algorithm on a graphics processing unit.

PubMed

Mei, Gang; Xu, Liangliang; Xu, Nengxiong

2017-09-01

This paper focuses on designing and implementing parallel adaptive inverse distance weighting (AIDW) interpolation algorithms by using the graphics processing unit (GPU). The AIDW is an improved version of the standard IDW, which can adaptively determine the power parameter according to the data points' spatial distribution pattern and achieve more accurate predictions than those predicted by IDW. In this paper, we first present two versions of the GPU-accelerated AIDW, i.e. the naive version without profiting from the shared memory and the tiled version taking advantage of the shared memory. We also implement the naive version and the tiled version using two data layouts, structure of arrays and array of aligned structures, on both single and double precision. We then evaluate the performance of parallel AIDW by comparing it with its corresponding serial algorithm on three different machines equipped with the GPUs GT730M, M5000 and K40c. The experimental results indicate that: (i) there is no significant difference in the computational efficiency when different data layouts are employed; (ii) the tiled version is always slightly faster than the naive version; and (iii) on single precision the achieved speed-up can be up to 763 (on the GPU M5000), while on double precision the obtained highest speed-up is 197 (on the GPU K40c). To benefit the community, all source code and testing data related to the presented parallel AIDW algorithm are publicly available.

Progressive Precision Surface Design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duchaineau, M; Joy, KJ

2002-01-11

We introduce a novel wavelet decomposition algorithm that makes a number of powerful new surface design operations practical. Wavelets, and hierarchical representations generally, have held promise to facilitate a variety of design tasks in a unified way by approximating results very precisely, thus avoiding a proliferation of undergirding mathematical representations. However, traditional wavelet decomposition is defined from fine to coarse resolution, thus limiting its efficiency for highly precise surface manipulation when attempting to create new non-local editing methods. Our key contribution is the progressive wavelet decomposition algorithm, a general-purpose coarse-to-fine method for hierarchical fitting, based in this paper on anmore » underlying multiresolution representation called dyadic splines. The algorithm requests input via a generic interval query mechanism, allowing a wide variety of non-local operations to be quickly implemented. The algorithm performs work proportionate to the tiny compressed output size, rather than to some arbitrarily high resolution that would otherwise be required, thus increasing performance by several orders of magnitude. We describe several design operations that are made tractable because of the progressive decomposition. Free-form pasting is a generalization of the traditional control-mesh edit, but for which the shape of the change is completely general and where the shape can be placed using a free-form deformation within the surface domain. Smoothing and roughening operations are enhanced so that an arbitrary loop in the domain specifies the area of effect. Finally, the sculpting effect of moving a tool shape along a path is simulated.« less

Topology optimisation of micro fluidic mixers considering fluid-structure interactions with a coupled Lattice Boltzmann algorithm

NASA Astrophysics Data System (ADS)

Munk, David J.; Kipouros, Timoleon; Vio, Gareth A.; Steven, Grant P.; Parks, Geoffrey T.

2017-11-01

Recently, the study of micro fluidic devices has gained much interest in various fields from biology to engineering. In the constant development cycle, the need to optimise the topology of the interior of these devices, where there are two or more optimality criteria, is always present. In this work, twin physical situations, whereby optimal fluid mixing in the form of vorticity maximisation is accompanied by the requirement that the casing in which the mixing takes place has the best structural performance in terms of the greatest specific stiffness, are considered. In the steady state of mixing this also means that the stresses in the casing are as uniform as possible, thus giving a desired operating life with minimum weight. The ultimate aim of this research is to couple two key disciplines, fluids and structures, into a topology optimisation framework, which shows fast convergence for multidisciplinary optimisation problems. This is achieved by developing a bi-directional evolutionary structural optimisation algorithm that is directly coupled to the Lattice Boltzmann method, used for simulating the flow in the micro fluidic device, for the objectives of minimum compliance and maximum vorticity. The needs for the exploration of larger design spaces and to produce innovative designs make meta-heuristic algorithms, such as genetic algorithms, particle swarms and Tabu Searches, less efficient for this task. The multidisciplinary topology optimisation framework presented in this article is shown to increase the stiffness of the structure from the datum case and produce physically acceptable designs. Furthermore, the topology optimisation method outperforms a Tabu Search algorithm in designing the baffle to maximise the mixing of the two fluids.

Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting

NASA Astrophysics Data System (ADS)

Zhang, Ningning; Lin, Aijing; Shang, Pengjian

2017-07-01

In this paper, we propose a new two-stage methodology that combines the ensemble empirical mode decomposition (EEMD) with multidimensional k-nearest neighbor model (MKNN) in order to forecast the closing price and high price of the stocks simultaneously. The modified algorithm of k-nearest neighbors (KNN) has an increasingly wide application in the prediction of all fields. Empirical mode decomposition (EMD) decomposes a nonlinear and non-stationary signal into a series of intrinsic mode functions (IMFs), however, it cannot reveal characteristic information of the signal with much accuracy as a result of mode mixing. So ensemble empirical mode decomposition (EEMD), an improved method of EMD, is presented to resolve the weaknesses of EMD by adding white noise to the original data. With EEMD, the components with true physical meaning can be extracted from the time series. Utilizing the advantage of EEMD and MKNN, the new proposed ensemble empirical mode decomposition combined with multidimensional k-nearest neighbor model (EEMD-MKNN) has high predictive precision for short-term forecasting. Moreover, we extend this methodology to the case of two-dimensions to forecast the closing price and high price of the four stocks (NAS, S&P500, DJI and STI stock indices) at the same time. The results indicate that the proposed EEMD-MKNN model has a higher forecast precision than EMD-KNN, KNN method and ARIMA.

Sequential drug treatment algorithm for agitation and aggression in Alzheimer's and mixed dementia.

PubMed

Davies, Simon Jc; Burhan, Amer M; Kim, Donna; Gerretsen, Philip; Graff-Guerrero, Ariel; Woo, Vincent L; Kumar, Sanjeev; Colman, Sarah; Pollock, Bruce G; Mulsant, Benoit H; Rajji, Tarek K

2018-05-01

Behavioural and psychological symptoms of dementia (BPSD) include agitation and aggression in people with dementia. BPSD is common on inpatient psychogeriatric units and may prevent individuals from living at home or in residential/nursing home settings. Several drugs and non-pharmacological treatments have been shown to be effective in reducing behavioural and psychological symptoms of dementia. Algorithmic treatment may address the challenge of synthesizing this evidence-based knowledge. A multidisciplinary team created evidence-based algorithms for the treatment of behavioural and psychological symptoms of dementia. We present drug treatment algorithms for agitation and aggression associated with Alzheimer's and mixed Alzheimer's/vascular dementia. Drugs were appraised by psychiatrists based on strength of evidence of efficacy, time to onset of clinical effect, tolerability, ease of use, and efficacy for indications other than behavioural and psychological symptoms of dementia. After baseline assessment and discontinuation of potentially exacerbating medications, sequential trials are recommended with risperidone, aripiprazole or quetiapine, carbamazepine, citalopram, gabapentin, and prazosin. Titration schedules are proposed, with adjustments for frailty. Additional guidance is given on use of electroconvulsive therapy, optimization of existing cholinesterase inhibitors/memantine, and use of pro re nata medications. This algorithm-based approach for drug treatment of agitation/aggression in Alzheimer's/mixed dementia has been implemented in several Canadian Hospital Inpatient Units. Impact should be assessed in future research.

A comparison of hydrographically and optically derived mixed layer depths

USGS Publications Warehouse

Zawada, D.G.; Zaneveld, J.R.V.; Boss, E.; Gardner, W.D.; Richardson, M.J.; Mishonov, A.V.

2005-01-01

Efforts to understand and model the dynamics of the upper ocean would be significantly advanced given the ability to rapidly determine mixed layer depths (MLDs) over large regions. Remote sensing technologies are an ideal choice for achieving this goal. This study addresses the feasibility of estimating MLDs from optical properties. These properties are strongly influenced by suspended particle concentrations, which generally reach a maximum at pycnoclines. The premise therefore is to use a gradient in beam attenuation at 660 nm (c660) as a proxy for the depth of a particle-scattering layer. Using a global data set collected during World Ocean Circulation Experiment cruises from 1988-1997, six algorithms were employed to compute MLDs from either density or temperature profiles. Given the absence of published optically based MLD algorithms, two new methods were developed that use c660 profiles to estimate the MLD. Intercomparison of the six hydrographically based algorithms revealed some significant disparities among the resulting MLD values. Comparisons between the hydrographical and optical approaches indicated a first-order agreement between the MLDs based on the depths of gradient maxima for density and c660. When comparing various hydrographically based algorithms, other investigators reported that inherent fluctuations of the mixed layer depth limit the accuracy of its determination to 20 m. Using this benchmark, we found a ???70% agreement between the best hydrographical-optical algorithm pairings. Copyright 2005 by the American Geophysical Union.

Robust and fast nonlinear optimization of diffusion MRI microstructure models.

PubMed

Harms, R L; Fritz, F J; Tobisch, A; Goebel, R; Roebroeck, A

2017-07-15

Advances in biophysical multi-compartment modeling for diffusion MRI (dMRI) have gained popularity because of greater specificity than DTI in relating the dMRI signal to underlying cellular microstructure. A large range of these diffusion microstructure models have been developed and each of the popular models comes with its own, often different, optimization algorithm, noise model and initialization strategy to estimate its parameter maps. Since data fit, accuracy and precision is hard to verify, this creates additional challenges to comparability and generalization of results from diffusion microstructure models. In addition, non-linear optimization is computationally expensive leading to very long run times, which can be prohibitive in large group or population studies. In this technical note we investigate the performance of several optimization algorithms and initialization strategies over a few of the most popular diffusion microstructure models, including NODDI and CHARMED. We evaluate whether a single well performing optimization approach exists that could be applied to many models and would equate both run time and fit aspects. All models, algorithms and strategies were implemented on the Graphics Processing Unit (GPU) to remove run time constraints, with which we achieve whole brain dataset fits in seconds to minutes. We then evaluated fit, accuracy, precision and run time for different models of differing complexity against three common optimization algorithms and three parameter initialization strategies. Variability of the achieved quality of fit in actual data was evaluated on ten subjects of each of two population studies with a different acquisition protocol. We find that optimization algorithms and multi-step optimization approaches have a considerable influence on performance and stability over subjects and over acquisition protocols. The gradient-free Powell conjugate-direction algorithm was found to outperform other common algorithms in terms of run time, fit, accuracy and precision. Parameter initialization approaches were found to be relevant especially for more complex models, such as those involving several fiber orientations per voxel. For these, a fitting cascade initializing or fixing parameter values in a later optimization step from simpler models in an earlier optimization step further improved run time, fit, accuracy and precision compared to a single step fit. This establishes and makes available standards by which robust fit and accuracy can be achieved in shorter run times. This is especially relevant for the use of diffusion microstructure modeling in large group or population studies and in combining microstructure parameter maps with tractography results. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A multi-objective genetic algorithm for a mixed-model assembly U-line balancing type-I problem considering human-related issues, training, and learning

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Montazeri, Mona; Farrokhi-Asl, Hamed; Rafiei, Hamed

2016-12-01

Mixed-model assembly lines are increasingly accepted in many industrial environments to meet the growing trend of greater product variability, diversification of customer demands, and shorter life cycles. In this research, a new mathematical model is presented considering balancing a mixed-model U-line and human-related issues, simultaneously. The objective function consists of two separate components. The first part of the objective function is related to balance problem. In this part, objective functions are minimizing the cycle time, minimizing the number of workstations, and maximizing the line efficiencies. The second part is related to human issues and consists of hiring cost, firing cost, training cost, and salary. To solve the presented model, two well-known multi-objective evolutionary algorithms, namely non-dominated sorting genetic algorithm and multi-objective particle swarm optimization, have been used. A simple solution representation is provided in this paper to encode the solutions. Finally, the computational results are compared and analyzed.

Development and Validation of Various Phenotyping Algorithms for Diabetes Mellitus Using Data from Electronic Health Records.

PubMed

Esteban, Santiago; Rodríguez Tablado, Manuel; Peper, Francisco; Mahumud, Yamila S; Ricci, Ricardo I; Kopitowski, Karin; Terrasa, Sergio

2017-01-01

Precision medicine requires extremely large samples. Electronic health records (EHR) are thought to be a cost-effective source of data for that purpose. Phenotyping algorithms help reduce classification errors, making EHR a more reliable source of information for research. Four algorithm development strategies for classifying patients according to their diabetes status (diabetics; non-diabetics; inconclusive) were tested (one codes-only algorithm; one boolean algorithm, four statistical learning algorithms and six stacked generalization meta-learners). The best performing algorithms within each strategy were tested on the validation set. The stacked generalization algorithm yielded the highest Kappa coefficient value in the validation set (0.95 95% CI 0.91, 0.98). The implementation of these algorithms allows for the exploitation of data from thousands of patients accurately, greatly reducing the costs of constructing retrospective cohorts for research.

Artificial intelligence, physiological genomics, and precision medicine.

PubMed

Williams, Anna Marie; Liu, Yong; Regner, Kevin R; Jotterand, Fabrice; Liu, Pengyuan; Liang, Mingyu

2018-04-01

Big data are a major driver in the development of precision medicine. Efficient analysis methods are needed to transform big data into clinically-actionable knowledge. To accomplish this, many researchers are turning toward machine learning (ML), an approach of artificial intelligence (AI) that utilizes modern algorithms to give computers the ability to learn. Much of the effort to advance ML for precision medicine has been focused on the development and implementation of algorithms and the generation of ever larger quantities of genomic sequence data and electronic health records. However, relevance and accuracy of the data are as important as quantity of data in the advancement of ML for precision medicine. For common diseases, physiological genomic readouts in disease-applicable tissues may be an effective surrogate to measure the effect of genetic and environmental factors and their interactions that underlie disease development and progression. Disease-applicable tissue may be difficult to obtain, but there are important exceptions such as kidney needle biopsy specimens. As AI continues to advance, new analytical approaches, including those that go beyond data correlation, need to be developed and ethical issues of AI need to be addressed. Physiological genomic readouts in disease-relevant tissues, combined with advanced AI, can be a powerful approach for precision medicine for common diseases.

Automated Design Tools for Integrated Mixed-Signal Microsystems (NeoCAD)

DTIC Science & Technology

2005-02-01

method, Model Order Reduction (MOR) tools, system-level, mixed-signal circuit synthesis and optimization tools, and parsitic extraction tools. A unique...Mission Area: Command and Control mixed signal circuit simulation parasitic extraction time-domain simulation IC design flow model order reduction... Extraction 1.2 Overall Program Milestones CHAPTER 2 FAST TIME DOMAIN MIXED-SIGNAL CIRCUIT SIMULATION 2.1 HAARSPICE Algorithms 2.1.1 Mathematical Background

GAMETES: a fast, direct algorithm for generating pure, strict, epistatic models with random architectures.

PubMed

Urbanowicz, Ryan J; Kiralis, Jeff; Sinnott-Armstrong, Nicholas A; Heberling, Tamra; Fisher, Jonathan M; Moore, Jason H

2012-10-01

Geneticists who look beyond single locus disease associations require additional strategies for the detection of complex multi-locus effects. Epistasis, a multi-locus masking effect, presents a particular challenge, and has been the target of bioinformatic development. Thorough evaluation of new algorithms calls for simulation studies in which known disease models are sought. To date, the best methods for generating simulated multi-locus epistatic models rely on genetic algorithms. However, such methods are computationally expensive, difficult to adapt to multiple objectives, and unlikely to yield models with a precise form of epistasis which we refer to as pure and strict. Purely and strictly epistatic models constitute the worst-case in terms of detecting disease associations, since such associations may only be observed if all n-loci are included in the disease model. This makes them an attractive gold standard for simulation studies considering complex multi-locus effects. We introduce GAMETES, a user-friendly software package and algorithm which generates complex biallelic single nucleotide polymorphism (SNP) disease models for simulation studies. GAMETES rapidly and precisely generates random, pure, strict n-locus models with specified genetic constraints. These constraints include heritability, minor allele frequencies of the SNPs, and population prevalence. GAMETES also includes a simple dataset simulation strategy which may be utilized to rapidly generate an archive of simulated datasets for given genetic models. We highlight the utility and limitations of GAMETES with an example simulation study using MDR, an algorithm designed to detect epistasis. GAMETES is a fast, flexible, and precise tool for generating complex n-locus models with random architectures. While GAMETES has a limited ability to generate models with higher heritabilities, it is proficient at generating the lower heritability models typically used in simulation studies evaluating new algorithms. In addition, the GAMETES modeling strategy may be flexibly combined with any dataset simulation strategy. Beyond dataset simulation, GAMETES could be employed to pursue theoretical characterization of genetic models and epistasis.

A Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks.

PubMed

Luo, Junhai; Fan, Liying

2017-03-30

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

A Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

PubMed Central

Luo, Junhai; Fan, Liying

2017-01-01

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization. PMID:28358342

Speed and path control for conflict-free flight in high air traffic demand in terminal airspace

NASA Astrophysics Data System (ADS)

Rezaei, Ali

To accommodate the growing air traffic demand, flights will need to be planned and navigated with a much higher level of precision than today's aircraft flight path. The Next Generation Air Transportation System (NextGen) stands to benefit significantly in safety and efficiency from such movement of aircraft along precisely defined paths. Air Traffic Operations (ATO) relying on such precision--the Precision Air Traffic Operations or PATO--are the foundation of high throughput capacity envisioned for the future airports. In PATO, the preferred method is to manage the air traffic by assigning a speed profile to each aircraft in a given fleet in a given airspace (in practice known as (speed control). In this research, an algorithm has been developed, set in the context of a Hybrid Control System (HCS) model, that determines whether a speed control solution exists for a given fleet of aircraft in a given airspace and if so, computes this solution as a collective speed profile that assures separation if executed without deviation. Uncertainties such as weather are not considered but the algorithm can be modified to include uncertainties. The algorithm first computes all feasible sequences (i.e., all sequences that allow the given fleet of aircraft to reach destinations without violating the FAA's separation requirement) by looking at all pairs of aircraft. Then, the most likely sequence is determined and the speed control solution is constructed by a backward trajectory generation, starting with the aircraft last out and proceeds to the first out. This computation can be done for different sequences in parallel which helps to reduce the computation time. If such a solution does not exist, then the algorithm calculates a minimal path modification (known as path control) that will allow separation-compliance speed control. We will also prove that the algorithm will modify the path without creating a new separation violation. The new path will be generated by adding new waypoints in the airspace. As a byproduct, instead of minimal path modification, one can use the aircraft arrival time schedule to generate the sequence in which the aircraft reach their destinations.

Improved liver R2* mapping by pixel-wise curve fitting with adaptive neighborhood regularization.

PubMed

Wang, Changqing; Zhang, Xinyuan; Liu, Xiaoyun; He, Taigang; Chen, Wufan; Feng, Qianjin; Feng, Yanqiu

2018-08-01

To improve liver R2* mapping by incorporating adaptive neighborhood regularization into pixel-wise curve fitting. Magnetic resonance imaging R2* mapping remains challenging because of the serial images with low signal-to-noise ratio. In this study, we proposed to exploit the neighboring pixels as regularization terms and adaptively determine the regularization parameters according to the interpixel signal similarity. The proposed algorithm, called the pixel-wise curve fitting with adaptive neighborhood regularization (PCANR), was compared with the conventional nonlinear least squares (NLS) and nonlocal means filter-based NLS algorithms on simulated, phantom, and in vivo data. Visually, the PCANR algorithm generates R2* maps with significantly reduced noise and well-preserved tiny structures. Quantitatively, the PCANR algorithm produces R2* maps with lower root mean square errors at varying R2* values and signal-to-noise-ratio levels compared with the NLS and nonlocal means filter-based NLS algorithms. For the high R2* values under low signal-to-noise-ratio levels, the PCANR algorithm outperforms the NLS and nonlocal means filter-based NLS algorithms in the accuracy and precision, in terms of mean and standard deviation of R2* measurements in selected region of interests, respectively. The PCANR algorithm can reduce the effect of noise on liver R2* mapping, and the improved measurement precision will benefit the assessment of hepatic iron in clinical practice. Magn Reson Med 80:792-801, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Kerr Reservoir LANDSAT experiment analysis for March 1981

NASA Technical Reports Server (NTRS)

Lecroy, S. R. (Principal Investigator)

1982-01-01

LANDSAT radiance data were used in an experiment conducted on the waters of Kerr Reservoir to determine if reliable algorithms could be developed that relate water quality parameters to remotely sensed data. A mix of different types of algorithms using the LANDSAT bands was generated to provide a thorough understanding of the relationships among the data involved. Except for secchi depth, the study demonstrated that for the ranges measured, the algorithms that satisfactorily represented the data encompass a mix of linear and nonlinear forms using only one LANDSAT band. Ratioing techniques did not improve the results since the initial design of the experiment minimized the errors against which this procedure is effective. Good correlations were found for total suspended solids, iron, turbidity, and secchi depth. Marginal correlations were discovered for nitrate and tannin + lignin. Quantification maps of Kerr Reservoir are presented for many of the water quality parameters using the developed algorithms.

LDA boost classification: boosting by topics

NASA Astrophysics Data System (ADS)

Lei, La; Qiao, Guo; Qimin, Cao; Qitao, Li

2012-12-01

AdaBoost is an efficacious classification algorithm especially in text categorization (TC) tasks. The methodology of setting up a classifier committee and voting on the documents for classification can achieve high categorization precision. However, traditional Vector Space Model can easily lead to the curse of dimensionality and feature sparsity problems; so it affects classification performance seriously. This article proposed a novel classification algorithm called LDABoost based on boosting ideology which uses Latent Dirichlet Allocation (LDA) to modeling the feature space. Instead of using words or phrase, LDABoost use latent topics as the features. In this way, the feature dimension is significantly reduced. Improved Naïve Bayes (NB) is designed as the weaker classifier which keeps the efficiency advantage of classic NB algorithm and has higher precision. Moreover, a two-stage iterative weighted method called Cute Integration in this article is proposed for improving the accuracy by integrating weak classifiers into strong classifier in a more rational way. Mutual Information is used as metrics of weights allocation. The voting information and the categorization decision made by basis classifiers are fully utilized for generating the strong classifier. Experimental results reveals LDABoost making categorization in a low-dimensional space, it has higher accuracy than traditional AdaBoost algorithms and many other classic classification algorithms. Moreover, its runtime consumption is lower than different versions of AdaBoost, TC algorithms based on support vector machine and Neural Networks.

Duplicate document detection in DocBrowse

NASA Astrophysics Data System (ADS)

Chalana, Vikram; Bruce, Andrew G.; Nguyen, Thien

1998-04-01

Duplicate documents are frequently found in large databases of digital documents, such as those found in digital libraries or in the government declassification effort. Efficient duplicate document detection is important not only to allow querying for similar documents, but also to filter out redundant information in large document databases. We have designed three different algorithm to identify duplicate documents. The first algorithm is based on features extracted from the textual content of a document, the second algorithm is based on wavelet features extracted from the document image itself, and the third algorithm is a combination of the first two. These algorithms are integrated within the DocBrowse system for information retrieval from document images which is currently under development at MathSoft. DocBrowse supports duplicate document detection by allowing (1) automatic filtering to hide duplicate documents, and (2) ad hoc querying for similar or duplicate documents. We have tested the duplicate document detection algorithms on 171 documents and found that text-based method has an average 11-point precision of 97.7 percent while the image-based method has an average 11- point precision of 98.9 percent. However, in general, the text-based method performs better when the document contains enough high-quality machine printed text while the image- based method performs better when the document contains little or no quality machine readable text.

Computational complexity of ecological and evolutionary spatial dynamics

PubMed Central

Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

2015-01-01

There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

Root System Water Consumption Pattern Identification on Time Series Data

PubMed Central

Figueroa, Manuel; Pope, Christopher

2017-01-01

In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers’ detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system’s 0.348 precision. PMID:28621739

Root System Water Consumption Pattern Identification on Time Series Data.

PubMed

Figueroa, Manuel; Pope, Christopher

2017-06-16

In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers' detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system's 0.348 precision.

A Robust Vehicle Localization Approach Based on GNSS/IMU/DMI/LiDAR Sensor Fusion for Autonomous Vehicles

PubMed Central

Meng, Xiaoli

2017-01-01

Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization. PMID:28926996

Satellite image processing for precision agriculture and agroindustry using convolutional neural network and genetic algorithm

NASA Astrophysics Data System (ADS)

Firdaus; Arkeman, Y.; Buono, A.; Hermadi, I.

2017-01-01

Translating satellite imagery to a useful data for decision making during this time are usually done manually by human. In this research, we are going to translate satellite imagery by using artificial intelligence method specifically using convolutional neural network and genetic algorithm to become a useful data for decision making, especially for precision agriculture and agroindustry. In this research, we are focused on how to made a sustainable land use planning with 3 objectives. The first is maximizing economic factor. Second is minimizing CO2 emission and the last is minimizing land degradation. Results show that by using artificial intelligence method, can produced a good pareto optimum solutions in a short time.

A Robust Vehicle Localization Approach Based on GNSS/IMU/DMI/LiDAR Sensor Fusion for Autonomous Vehicles.

PubMed

Meng, Xiaoli; Wang, Heng; Liu, Bingbing

2017-09-18

Precise and robust localization in a large-scale outdoor environment is essential for an autonomous vehicle. In order to improve the performance of the fusion of GNSS (Global Navigation Satellite System)/IMU (Inertial Measurement Unit)/DMI (Distance-Measuring Instruments), a multi-constraint fault detection approach is proposed to smooth the vehicle locations in spite of GNSS jumps. Furthermore, the lateral localization error is compensated by the point cloud-based lateral localization method proposed in this paper. Experiment results have verified the algorithms proposed in this paper, which shows that the algorithms proposed in this paper are capable of providing precise and robust vehicle localization.

Study on optimized algorithm for mileage wheel of magnetic flux leakage detector

NASA Astrophysics Data System (ADS)

Y Sun, L.; Li, Y. B.; Wu, Y. T.; Y Xu, Q.; Cai, Y.

2017-07-01

Pipeline integrity is significant to safe operation of long-range pipeline. To avoid critical failure of the pipeline, which may lead to great loss of property and life, MFL_PIG is often used to detect the corrosion and leakage of the pipeline. To accurately locate the defects, mileage pulses emitted by the mileage wheel are used to and emit signal to single-chip microcomputer for position. This paper investigates the factors that may affect the precision of mileage wheel, an important part of pipeline corrosion and leakage detector (MFL_PIG), investigate its working principle and present an optimized algorithm for mileage wheel to increase the precision of detection.

An Overview of the Formation and Attitude Control System for the Terrestrial Planet Finder Formation Flying Interferometer

NASA Technical Reports Server (NTRS)

Scharf, Daniel P.; Hadaegh, Fred Y.; Rahman, Zahidul H.; Shields, Joel F.; Singh, Gurkipal; Wette, Matthew R.

2004-01-01

The Terrestrial Planet Finder formation flying Interferometer (TPF-I) will be a five-spacecraft, precision formation operating near the second Sun-Earth Lagrange point. As part of technology development for TPF-I, a formation and attitude control system (FACS) is being developed that achieves the precision and functionality needed for the TPF-I formation and that will be demonstrated in a distributed, real-time simulation environment. In this paper we present an overview of FACS and discuss in detail its formation estimation, guidance and control architectures and algorithms. Since FACS is currently being integrated into a high-fidelity simulation environment, component simulations demonstrating algorithm performance are presented.

An Overview of the Formation and Attitude Control System for the Terrestrial Planet Finder Formation Flying Interferometer

NASA Technical Reports Server (NTRS)

Scharf, Daniel P.; Hadaegh, Fred Y.; Rahman, Zahidul H.; Shields, Joel F.; Singh, Gurkipal

2004-01-01

The Terrestrial Planet Finder formation flying Interferometer (TPF-I) will be a five-spacecraft, precision formation operating near a Sun-Earth Lagrange point. As part of technology development for TPF-I, a formation and attitude control system (FACS) is being developed that achieves the precision and functionality associated with the TPF-I formation. This FACS will be demonstrated in a distributed, real-time simulation environment. In this paper we present an overview of the FACS and discuss in detail its constituent formation estimation, guidance and control architectures and algorithms. Since the FACS is currently being integrated into a high-fidelity simulation environment, component simulations demonstrating algorithm performance are presented.

A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

DOE PAGES

Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, Kevin K.; ...

2016-06-10

Knowledge of cloud phase (liquid, ice, mixed, etc.) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. In this study, we outline a methodology using a basic Bayesian classifier to estimate the probabilities of cloud-phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. The advantage of this method over previous ones is that it provides uncertainty informationmore » on the phase classification. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the method can be used to train an algorithm that identifies ice, liquid, mixed phase, and snow. Over 95 % of data are identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm. As a result, this is a first step towards an operational algorithm and can be expanded to include additional categories such as drizzle with additional training data.« less

A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

NASA Astrophysics Data System (ADS)

Riihimaki, Laura D.; Comstock, Jennifer M.; Anderson, Kevin K.; Holmes, Aimee; Luke, Edward

2016-06-01

Knowledge of cloud phase (liquid, ice, mixed, etc.) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. In this study, we outline a methodology using a basic Bayesian classifier to estimate the probabilities of cloud-phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. The advantage of this method over previous ones is that it provides uncertainty information on the phase classification. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the method can be used to train an algorithm that identifies ice, liquid, mixed phase, and snow. Over 95 % of data are identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm. This is a first step towards an operational algorithm and can be expanded to include additional categories such as drizzle with additional training data.

An application of artificial neural intelligence for personal dose assessment using a multi-area OSL dosimetry system.

PubMed

Lee, S Y; Kim, B H; Lee, K J

2001-06-01

Significant advances have been made in recent years to improve measurement technology and performance of phosphor materials in the fields of optically stimulated luminescence (OSL) dosimetry. Pulsed and continuous wave OSL studies recently carried out on alpha-Al2O3:C have shown that the material seems to be the most promising for routine application of OSL for dosimetric purposes. The main objective of the study is to propose a new personal dosimetry system using alpha-Al2O3:C by taking advantage of its optical properties and energy dependencies. In the process of the study, a new dose assessment algorithm was developed using artificial neural networks in hopes of achieving a higher degree of accuracy and precision in personal OSL dosimetry system. The original hypothesis of this work is that the spectral information of X- and gamma-ray fields may be obtained by the analysis of the response of a multi-element system. In this study, a feedforward neural network using the error back-propagation method with Bayesian optimization was applied for the response unfolding procedure. The validation of the proposed algorithm was investigated by unfolding the 10 measured responses of alpha-Al2O3:C for arbitrarily mixed photon fields which range from 20 to 662 keV. c2001 Elsevier Science Ltd. All rights reserved.

On-line dynamic monitoring automotive exhausts: using BP-ANN for distinguishing multi-components

NASA Astrophysics Data System (ADS)

Zhao, Yudi; Wei, Ruyi; Liu, Xuebin

2017-10-01

Remote sensing-Fourier Transform infrared spectroscopy (RS-FTIR) is one of the most important technologies in atmospheric pollutant monitoring. It is very appropriate for on-line dynamic remote sensing monitoring of air pollutants, especially for the automotive exhausts. However, their absorption spectra are often seriously overlapped in the atmospheric infrared window bands, i.e. MWIR (3 5μm). Artificial Neural Network (ANN) is an algorithm based on the theory of the biological neural network, which simplifies the partial differential equation with complex construction. For its preferable performance in nonlinear mapping and fitting, in this paper we utilize Back Propagation-Artificial Neural Network (BP-ANN) to quantitatively analyze the concentrations of four typical industrial automotive exhausts, including CO, NO, NO2 and SO2. We extracted the original data of these automotive exhausts from the HITRAN database, most of which virtually overlapped, and established a mixed multi-component simulation environment. Based on Beer-Lambert Law, concentrations can be retrieved from the absorbance of spectra. Parameters including learning rate, momentum factor, the number of hidden nodes and iterations were obtained when the BP network was trained with 80 groups of input data. By improving these parameters, the network can be optimized to produce necessarily higher precision for the retrieved concentrations. This BP-ANN method proves to be an effective and promising algorithm on dealing with multi-components analysis of automotive exhausts.

Measurement precision in a series of visual fields acquired by the standard and fast versions of the Swedish interactive thresholding algorithm: analysis of large-scale data from clinics.

PubMed

Saunders, Luke J; Russell, Richard A; Crabb, David P

2015-01-01

Swedish Interactive Thresholding Algorithm (SITA) testing strategies for the Humphrey Field Analyzer have become a clinical standard. Measurements from SITA Fast are thought to be more variable than SITA Standard, yet some clinics routinely use SITA Fast because it is quicker. To examine the measurement precision of the 2 SITA strategies across a range of sensitivities using a large number of visual field (VF) series from 4 glaucoma clinics in England. Retrospective cohort study at Moorfields Eye Hospital in London, England; Gloucestershire Eye Unit at Cheltenham General Hospital; Queen Alexandra Hospital in Portsmouth, England; and the Calderdale and Huddersfield National Health Service Foundation Trust that included 66,974 Humphrey 24-2 SITA Standard VFs (10,124 eyes) and 19,819 Humphrey 24-2 SITA Fast VFs (3654 eyes) recorded between May 20, 1997, and September 20, 2012. Pointwise ordinary least squares linear regression of measured sensitivity over time was conducted using VF series of 1 random eye from each patient. Residuals from the regression were pooled according to fitted sensitivities. For each sensitivity (decibel) level, the standard deviation of the residuals was used to estimate measurement precision and were compared for SITA Standard and SITA Fast. Simulations of progression from different VF baselines were used to evaluate how different levels of precision would affect time to detect VF progression. Median years required to detect progression. Median (interquartile range) patient age, follow-up, and series lengths for SITA Standard were 64 (53-72) years, 6.0 (4.0-8.5) years, and 6 (4-8) VFs, respectively; for SITA Fast, medians (interquartile range) were 70 (61-78) years, 5.1 (3.2-7.3) years, and 5 (4-6) VFs. Measurement precision worsened as sensitivity decreased for both test strategies. In the 20 to 5 dB range, SITA Fast was less precise than SITA Standard; this difference was largest between 15 to 10 dB, where variability in both methods peaked. Translated to median time to detection, differences in measurement precision were negligible, suggesting minimal effects on time to detect progression. Although SITA Standard is a more precise testing algorithm than SITA Fast at lower VF sensitivities, it is unlikely to make a sizeable difference to improving the time to detect VF progression.

Underwater terrain-aided navigation system based on combination matching algorithm.

PubMed

Li, Peijuan; Sheng, Guoliang; Zhang, Xiaofei; Wu, Jingqiu; Xu, Baochun; Liu, Xing; Zhang, Yao

2018-07-01

Considering that the terrain-aided navigation (TAN) system based on iterated closest contour point (ICCP) algorithm diverges easily when the indicative track of strapdown inertial navigation system (SINS) is large, Kalman filter is adopted in the traditional ICCP algorithm, difference between matching result and SINS output is used as the measurement of Kalman filter, then the cumulative error of the SINS is corrected in time by filter feedback correction, and the indicative track used in ICCP is improved. The mathematic model of the autonomous underwater vehicle (AUV) integrated into the navigation system and the observation model of TAN is built. Proper matching point number is designated by comparing the simulation results of matching time and matching precision. Simulation experiments are carried out according to the ICCP algorithm and the mathematic model. It can be concluded from the simulation experiments that the navigation accuracy and stability are improved with the proposed combinational algorithm in case that proper matching point number is engaged. It will be shown that the integrated navigation system is effective in prohibiting the divergence of the indicative track and can meet the requirements of underwater, long-term and high precision of the navigation system for autonomous underwater vehicles. Copyright © 2017. Published by Elsevier Ltd.

The optimal digital filters of sine and cosine transforms for geophysical transient electromagnetic method

NASA Astrophysics Data System (ADS)

Zhao, Yun-wei; Zhu, Zi-qiang; Lu, Guang-yin; Han, Bo

2018-03-01

The sine and cosine transforms implemented with digital filters have been used in the Transient electromagnetic methods for a few decades. Kong (2007) proposed a method of obtaining filter coefficients, which are computed in the sample domain by Hankel transform pair. However, the curve shape of Hankel transform pair changes with a parameter, which usually is set to be 1 or 3 in the process of obtaining the digital filter coefficients of sine and cosine transforms. First, this study investigates the influence of the parameter on the digital filter algorithm of sine and cosine transforms based on the digital filter algorithm of Hankel transform and the relationship between the sine, cosine function and the ±1/2 order Bessel function of the first kind. The results show that the selection of the parameter highly influences the precision of digital filter algorithm. Second, upon the optimal selection of the parameter, it is found that an optimal sampling interval s also exists to achieve the best precision of digital filter algorithm. Finally, this study proposes four groups of sine and cosine transform digital filter coefficients with different length, which may help to develop the digital filter algorithm of sine and cosine transforms, and promote its application.

A high-speed tracking algorithm for dense granular media

NASA Astrophysics Data System (ADS)

Cerda, Mauricio; Navarro, Cristóbal A.; Silva, Juan; Waitukaitis, Scott R.; Mujica, Nicolás; Hitschfeld, Nancy

2018-06-01

Many fields of study, including medical imaging, granular physics, colloidal physics, and active matter, require the precise identification and tracking of particle-like objects in images. While many algorithms exist to track particles in diffuse conditions, these often perform poorly when particles are densely packed together-as in, for example, solid-like systems of granular materials. Incorrect particle identification can have significant effects on the calculation of physical quantities, which makes the development of more precise and faster tracking algorithms a worthwhile endeavor. In this work, we present a new tracking algorithm to identify particles in dense systems that is both highly accurate and fast. We demonstrate the efficacy of our approach by analyzing images of dense, solid-state granular media, where we achieve an identification error of 5% in the worst evaluated cases. Going further, we propose a parallelization strategy for our algorithm using a GPU, which results in a speedup of up to 10 × when compared to a sequential CPU implementation in C and up to 40 × when compared to the reference MATLAB library widely used for particle tracking. Our results extend the capabilities of state-of-the-art particle tracking methods by allowing fast, high-fidelity detection in dense media at high resolutions.

IEEE 802.15.4 ZigBee-Based Time-of-Arrival Estimation for Wireless Sensor Networks.

PubMed

Cheon, Jeonghyeon; Hwang, Hyunsu; Kim, Dongsun; Jung, Yunho

2016-02-05

Precise time-of-arrival (TOA) estimation is one of the most important techniques in RF-based positioning systems that use wireless sensor networks (WSNs). Because the accuracy of TOA estimation is proportional to the RF signal bandwidth, using broad bandwidth is the most fundamental approach for achieving higher accuracy. Hence, ultra-wide-band (UWB) systems with a bandwidth of 500 MHz are commonly used. However, wireless systems with broad bandwidth suffer from the disadvantages of high complexity and high power consumption. Therefore, it is difficult to employ such systems in various WSN applications. In this paper, we present a precise time-of-arrival (TOA) estimation algorithm using an IEEE 802.15.4 ZigBee system with a narrow bandwidth of 2 MHz. In order to overcome the lack of bandwidth, the proposed algorithm estimates the fractional TOA within the sampling interval. Simulation results show that the proposed TOA estimation algorithm provides an accuracy of 0.5 m at a signal-to-noise ratio (SNR) of 8 dB and achieves an SNR gain of 5 dB as compared with the existing algorithm. In addition, experimental results indicate that the proposed algorithm provides accurate TOA estimation in a real indoor environment.

Adaptive mixed finite element methods for Darcy flow in fractured porous media

NASA Astrophysics Data System (ADS)

Chen, Huangxin; Salama, Amgad; Sun, Shuyu

2016-10-01

In this paper, we propose adaptive mixed finite element methods for simulating the single-phase Darcy flow in two-dimensional fractured porous media. The reduced model that we use for the simulation is a discrete fracture model coupling Darcy flows in the matrix and the fractures, and the fractures are modeled by one-dimensional entities. The Raviart-Thomas mixed finite element methods are utilized for the solution of the coupled Darcy flows in the matrix and the fractures. In order to improve the efficiency of the simulation, we use adaptive mixed finite element methods based on novel residual-based a posteriori error estimators. In addition, we develop an efficient upscaling algorithm to compute the effective permeability of the fractured porous media. Several interesting examples of Darcy flow in the fractured porous media are presented to demonstrate the robustness of the algorithm.

A Polyhedral Outer-approximation, Dynamic-discretization optimization solver, 1.x

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, Rusell; Nagarajan, Harsha; Sundar, Kaarthik

2017-09-25

In this software, we implement an adaptive, multivariate partitioning algorithm for solving mixed-integer nonlinear programs (MINLP) to global optimality. The algorithm combines ideas that exploit the structure of convex relaxations to MINLPs and bound tightening procedures

[A plane-based hand-eye calibration method for surgical robots].

PubMed

Zeng, Bowei; Meng, Fanle; Ding, Hui; Liu, Wenbo; Wu, Di; Wang, Guangzhi

2017-04-01

In order to calibrate the hand-eye transformation of the surgical robot and laser range finder (LRF), a calibration algorithm based on a planar template was designed. A mathematical model of the planar template had been given and the approach to address the equations had been derived. Aiming at the problems of the measurement error in a practical system, we proposed a new algorithm for selecting coplanar data. This algorithm can effectively eliminate considerable measurement error data to improve the calibration accuracy. Furthermore, three orthogonal planes were used to improve the calibration accuracy, in which a nonlinear optimization for hand-eye calibration was used. With the purpose of verifying the calibration precision, we used the LRF to measure some fixed points in different directions and a cuboid's surfaces. Experimental results indicated that the precision of a single planar template method was (1.37±0.24) mm, and that of the three orthogonal planes method was (0.37±0.05) mm. Moreover, the mean FRE of three-dimensional (3D) points was 0.24 mm and mean TRE was 0.26 mm. The maximum angle measurement error was 0.4 degree. Experimental results show that the method presented in this paper is effective with high accuracy and can meet the requirements of surgical robot precise location.

A classification of user-generated content into consumer decision journey stages.

PubMed

Vázquez, Silvia; Muñoz-García, Óscar; Campanella, Inés; Poch, Marc; Fisas, Beatriz; Bel, Nuria; Andreu, Gloria

2014-10-01

In the last decades, the availability of digital user-generated documents from social media has dramatically increased. This massive growth of user-generated content has also affected traditional shopping behaviour. Customers have embraced new communication channels such as microblogs and social networks that enable them not only just to talk with friends and acquaintances about their shopping experience, but also to search for opinions expressed by complete strangers as part of their decision making processes. Uncovering how customers feel about specific products or brands and detecting purchase habits and preferences has traditionally been a costly and highly time-consuming task which involved the use of methods such as focus groups and surveys. However, the new scenario calls for a deep assessment of current market research techniques in order to better interpret and profit from this ever-growing stream of attitudinal data. With this purpose, we present a novel analysis and classification of user-generated content in terms of it belonging to one of the four stages of the Consumer Decision Journey Court et al. (2009) (i.e. the purchase process from the moment when a customer is aware of the existence of the product to the moment when he or she buys, experiences and talks about it). Using a corpus of short texts written in English and Spanish and extracted from different social media, we identify a set of linguistic patterns for each purchase stage that will be then used in a rule-based classifier. Additionally, we use machine learning algorithms to automatically identify business indicators such as the Marketing Mix elements McCarthy and Brogowicz (1981). The classification of the purchase stages achieves an average precision of 74%. The proposed classification of texts depending on the Marketing Mix elements expressed achieved an average precision of 75% for all the elements analysed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Global optimization of small bimetallic Pd-Co binary nanoalloy clusters: a genetic algorithm approach at the DFT level.

PubMed

Aslan, Mikail; Davis, Jack B A; Johnston, Roy L

2016-03-07

The global optimisation of small bimetallic PdCo binary nanoalloys are systematically investigated using the Birmingham Cluster Genetic Algorithm (BCGA). The effect of size and composition on the structures, stability, magnetic and electronic properties including the binding energies, second finite difference energies and mixing energies of Pd-Co binary nanoalloys are discussed. A detailed analysis of Pd-Co structural motifs and segregation effects is also presented. The maximal mixing energy corresponds to Pd atom compositions for which the number of mixed Pd-Co bonds is maximised. Global minimum clusters are distinguished from transition states by vibrational frequency analysis. HOMO-LUMO gap, electric dipole moment and vibrational frequency analyses are made to enable correlation with future experiments.

Compression of multispectral Landsat imagery using the Embedded Zerotree Wavelet (EZW) algorithm

NASA Technical Reports Server (NTRS)

Shapiro, Jerome M.; Martucci, Stephen A.; Czigler, Martin

1994-01-01

The Embedded Zerotree Wavelet (EZW) algorithm has proven to be an extremely efficient and flexible compression algorithm for low bit rate image coding. The embedding algorithm attempts to order the bits in the bit stream in numerical importance and thus a given code contains all lower rate encodings of the same algorithm. Therefore, precise bit rate control is achievable and a target rate or distortion metric can be met exactly. Furthermore, the technique is fully image adaptive. An algorithm for multispectral image compression which combines the spectral redundancy removal properties of the image-dependent Karhunen-Loeve Transform (KLT) with the efficiency, controllability, and adaptivity of the embedded zerotree wavelet algorithm is presented. Results are shown which illustrate the advantage of jointly encoding spectral components using the KLT and EZW.

Optimal Control of Evolution Mixed Variational Inclusions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alduncin, Gonzalo, E-mail: alduncin@geofisica.unam.mx

2013-12-15

Optimal control problems of primal and dual evolution mixed variational inclusions, in reflexive Banach spaces, are studied. The solvability analysis of the mixed state systems is established via duality principles. The optimality analysis is performed in terms of perturbation conjugate duality methods, and proximation penalty-duality algorithms to mixed optimality conditions are further presented. Applications to nonlinear diffusion constrained problems as well as quasistatic elastoviscoplastic bilateral contact problems exemplify the theory.

Measurement of the Effective Weak Mixing Angle in $$p\\bar{p} \\to Z/\\gamma^* \\to e^+e^-$$ events at $$\\sqrt{s} = 1.96$$ TeV

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Siqi

2016-01-01

We present a measurement of the fundamental parameter of the standard model, the weak mixing angle, in pp¯→Z/γ∗→e+e− events at a center of mass energy of 1.96 TeV, using data corresponding to 9.7 fb−1 of integrated luminosity collected by the D0 detector at the Fermilab Tevatron. The effective weak mixing angle is extracted from the forward-backward charge asymmetry as a function of the invariant mass around the Z boson pole. The measured value of sin2θℓeff=0.23147±0.00047 is the most precise measurement from light quark interactions to date, with a precision close to the best LEP and SLD results.

Precise determination of lattice phase shifts and mixing angles

DOE PAGES

Lu, Bing -Nan; Lähde, Timo A.; Lee, Dean; ...

2016-07-09

Here, we introduce a general and accurate method for determining lattice phase shifts and mixing angles, which is applicable to arbitrary, non-cubic lattices. Our method combines angular momentum projection, spherical wall boundaries and an adjustable auxiliary potential. This allows us to construct radial lattice wave functions and to determine phase shifts at arbitrary energies. For coupled partial waves, we use a complex-valued auxiliary potential that breaks time-reversal invariance. We benchmark our method using a system of two spin-1/2 particles interacting through a finite-range potential with a strong tensor component. We are able to extract phase shifts and mixing angles formore » all angular momenta and energies, with precision greater than that of extant methods. We discuss a wide range of applications from nuclear lattice simulations to optical lattice experiments.« less

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Fourth Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2013-01-01

This paper presents an overview of the fourth major revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. Because this algorithm is trajectory-based, it also has the inherent ability to support required-time-of-arrival (RTA) operations. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. Revisions to this algorithm were based on a change to the expected operational environment.

Assessment of various supervised learning algorithms using different performance metrics

NASA Astrophysics Data System (ADS)

Susheel Kumar, S. M.; Laxkar, Deepak; Adhikari, Sourav; Vijayarajan, V.

2017-11-01

Our work brings out comparison based on the performance of supervised machine learning algorithms on a binary classification task. The supervised machine learning algorithms which are taken into consideration in the following work are namely Support Vector Machine(SVM), Decision Tree(DT), K Nearest Neighbour (KNN), Naïve Bayes(NB) and Random Forest(RF). This paper mostly focuses on comparing the performance of above mentioned algorithms on one binary classification task by analysing the Metrics such as Accuracy, F-Measure, G-Measure, Precision, Misclassification Rate, False Positive Rate, True Positive Rate, Specificity, Prevalence.

CAD system for footwear design based on whole real 3D data of last surface

NASA Astrophysics Data System (ADS)

Song, Wanzhong; Su, Xianyu

2000-10-01

Two major parts of application of CAD in footwear design are studied: the development of last surface; computer-aided design of planar shoe-template. A new quasi-experiential development algorithm of last surface based on triangulation approximation is presented. This development algorithm consumes less time and does not need any interactive operation for precisely development compared with other development algorithm of last surface. Based on this algorithm, a software, SHOEMAKERTM, which contains computer aided automatic measurement, automatic development of last surface and computer aide design of shoe-template has been developed.

Stochastic optimization algorithms for barrier dividend strategies

NASA Astrophysics Data System (ADS)

Yin, G.; Song, Q. S.; Yang, H.

2009-01-01

This work focuses on finding optimal barrier policy for an insurance risk model when the dividends are paid to the share holders according to a barrier strategy. A new approach based on stochastic optimization methods is developed. Compared with the existing results in the literature, more general surplus processes are considered. Precise models of the surplus need not be known; only noise-corrupted observations of the dividends are used. Using barrier-type strategies, a class of stochastic optimization algorithms are developed. Convergence of the algorithm is analyzed; rate of convergence is also provided. Numerical results are reported to demonstrate the performance of the algorithm.

Estimation of TOA based MUSIC algorithm and cross correlation algorithm of appropriate interval

NASA Astrophysics Data System (ADS)

Lin, Wei; Liu, Jun; Zhou, Yineng; Huang, Jiyan

2017-03-01

Localization of mobile station (MS) has now gained considerable attention due to its wide applications in military, environmental, health and commercial systems. Phrase angle and encode data of MSK system model are two critical parameters in time-of-arrival (TOA) localization technique; nevertheless, precise value of phrase angle and encode data are not easy to achieved in general. In order to meet the actual situation, we should consider the condition that phase angle and encode data is unknown. In this paper, a novel TOA localization method, which combine MUSIC algorithm and cross correlation algorithm in an appropriate interval, is proposed. Simulations show that the proposed method has better performance than music algorithm and cross correlation algorithm of the whole interval.

Research on the precise positioning of customers in large data environment

NASA Astrophysics Data System (ADS)

Zhou, Xu; He, Lili

2018-04-01

Customer positioning has always been a problem that enterprises focus on. In this paper, FCM clustering algorithm is used to cluster customer groups. However, due to the traditional FCM clustering algorithm, which is susceptible to the influence of the initial clustering center and easy to fall into the local optimal problem, the short board of FCM is solved by the gray optimization algorithm (GWO) to achieve efficient and accurate handling of a large number of retailer data.

N-of-1-pathways MixEnrich: advancing precision medicine via single-subject analysis in discovering dynamic changes of transcriptomes.

PubMed

Li, Qike; Schissler, A Grant; Gardeux, Vincent; Achour, Ikbel; Kenost, Colleen; Berghout, Joanne; Li, Haiquan; Zhang, Hao Helen; Lussier, Yves A

2017-05-24

Transcriptome analytic tools are commonly used across patient cohorts to develop drugs and predict clinical outcomes. However, as precision medicine pursues more accurate and individualized treatment decisions, these methods are not designed to address single-patient transcriptome analyses. We previously developed and validated the N-of-1-pathways framework using two methods, Wilcoxon and Mahalanobis Distance (MD), for personal transcriptome analysis derived from a pair of samples of a single patient. Although, both methods uncover concordantly dysregulated pathways, they are not designed to detect dysregulated pathways with up- and down-regulated genes (bidirectional dysregulation) that are ubiquitous in biological systems. We developed N-of-1-pathways MixEnrich, a mixture model followed by a gene set enrichment test, to uncover bidirectional and concordantly dysregulated pathways one patient at a time. We assess its accuracy in a comprehensive simulation study and in a RNA-Seq data analysis of head and neck squamous cell carcinomas (HNSCCs). In presence of bidirectionally dysregulated genes in the pathway or in presence of high background noise, MixEnrich substantially outperforms previous single-subject transcriptome analysis methods, both in the simulation study and the HNSCCs data analysis (ROC Curves; higher true positive rates; lower false positive rates). Bidirectional and concordant dysregulated pathways uncovered by MixEnrich in each patient largely overlapped with the quasi-gold standard compared to other single-subject and cohort-based transcriptome analyses. The greater performance of MixEnrich presents an advantage over previous methods to meet the promise of providing accurate personal transcriptome analysis to support precision medicine at point of care.

DISCRETE VOLUME-ELEMENT METHOD FOR NETWORK WATER- QUALITY MODELS

EPA Science Inventory

An explicit dynamic water-quality modeling algorithm is developed for tracking dissolved substances in water-distribution networks. The algorithm is based on a mass-balance relation within pipes that considers both advective transport and reaction kinetics. Complete mixing of m...

Altimeter measurements for the determination of the Earth's gravity field

NASA Technical Reports Server (NTRS)

Tapley, B. D.; Schutz, B. E.; Shum, C. K.

1986-01-01

Progress in the following areas is described: refining altimeter and altimeter crossover measurement models for precise orbit determination and for the solution of the earth's gravity field; performing experiments using altimeter data for the improvement of precise satellite ephemerides; and analyzing an optimal relative data weighting algorithm to combine various data types in the solution of the gravity field.

CT image reconstruction with half precision floating-point values.

PubMed

Maaß, Clemens; Baer, Matthias; Kachelrieß, Marc

2011-07-01

Analytic CT image reconstruction is a computationally demanding task. Currently, the even more demanding iterative reconstruction algorithms find their way into clinical routine because their image quality is superior to analytic image reconstruction. The authors thoroughly analyze a so far unconsidered but valuable tool of tomorrow's reconstruction hardware (CPU and GPU) that allows implementing the forward projection and backprojection steps, which are the computationally most demanding parts of any reconstruction algorithm, much more efficiently. Instead of the standard 32 bit floating-point values (float), a recently standardized floating-point value with 16 bit (half) is adopted for data representation in image domain and in rawdata domain. The reduction in the total data amount reduces the traffic on the memory bus, which is the bottleneck of today's high-performance algorithms, by 50%. In CT simulations and CT measurements, float reconstructions (gold standard) and half reconstructions are visually compared via difference images and by quantitative image quality evaluation. This is done for analytical reconstruction (filtered backprojection) and iterative reconstruction (ordered subset SART). The magnitude of quantization noise, which is caused by a reduction in the data precision of both rawdata and image data during image reconstruction, is negligible. This is clearly shown for filtered backprojection and iterative ordered subset SART reconstruction. In filtered backprojection, the implementation of the backprojection should be optimized for low data precision if the image data are represented in half format. In ordered subset SART image reconstruction, no adaptations are necessary and the convergence speed remains unchanged. Half precision floating-point values allow to speed up CT image reconstruction without compromising image quality.

Computing Generalized Matrix Inverse on Spiking Neural Substrate.

PubMed

Shukla, Rohit; Khoram, Soroosh; Jorgensen, Erik; Li, Jing; Lipasti, Mikko; Wright, Stephen

2018-01-01

Emerging neural hardware substrates, such as IBM's TrueNorth Neurosynaptic System, can provide an appealing platform for deploying numerical algorithms. For example, a recurrent Hopfield neural network can be used to find the Moore-Penrose generalized inverse of a matrix, thus enabling a broad class of linear optimizations to be solved efficiently, at low energy cost. However, deploying numerical algorithms on hardware platforms that severely limit the range and precision of representation for numeric quantities can be quite challenging. This paper discusses these challenges and proposes a rigorous mathematical framework for reasoning about range and precision on such substrates. The paper derives techniques for normalizing inputs and properly quantizing synaptic weights originating from arbitrary systems of linear equations, so that solvers for those systems can be implemented in a provably correct manner on hardware-constrained neural substrates. The analytical model is empirically validated on the IBM TrueNorth platform, and results show that the guarantees provided by the framework for range and precision hold under experimental conditions. Experiments with optical flow demonstrate the energy benefits of deploying a reduced-precision and energy-efficient generalized matrix inverse engine on the IBM TrueNorth platform, reflecting 10× to 100× improvement over FPGA and ARM core baselines.

Easy-DHPSF open-source software for three-dimensional localization of single molecules with precision beyond the optical diffraction limit.

PubMed

Lew, Matthew D; von Diezmann, Alexander R S; Moerner, W E

2013-02-25

Automated processing of double-helix (DH) microscope images of single molecules (SMs) streamlines the protocol required to obtain super-resolved three-dimensional (3D) reconstructions of ultrastructures in biological samples by single-molecule active control microscopy. Here, we present a suite of MATLAB subroutines, bundled with an easy-to-use graphical user interface (GUI), that facilitates 3D localization of single emitters (e.g. SMs, fluorescent beads, or quantum dots) with precisions of tens of nanometers in multi-frame movies acquired using a wide-field DH epifluorescence microscope. The algorithmic approach is based upon template matching for SM recognition and least-squares fitting for 3D position measurement, both of which are computationally expedient and precise. Overlapping images of SMs are ignored, and the precision of least-squares fitting is not as high as maximum likelihood-based methods. However, once calibrated, the algorithm can fit 15-30 molecules per second on a 3 GHz Intel Core 2 Duo workstation, thereby producing a 3D super-resolution reconstruction of 100,000 molecules over a 20×20×2 μm field of view (processing 128×128 pixels × 20000 frames) in 75 min.

Underestimation of Variance of Predicted Health Utilities Derived from Multiattribute Utility Instruments.

PubMed

Chan, Kelvin K W; Xie, Feng; Willan, Andrew R; Pullenayegum, Eleanor M

2017-04-01

Parameter uncertainty in value sets of multiattribute utility-based instruments (MAUIs) has received little attention previously. This false precision leads to underestimation of the uncertainty of the results of cost-effectiveness analyses. The aim of this study is to examine the use of multiple imputation as a method to account for this uncertainty of MAUI scoring algorithms. We fitted a Bayesian model with random effects for respondents and health states to the data from the original US EQ-5D-3L valuation study, thereby estimating the uncertainty in the EQ-5D-3L scoring algorithm. We applied these results to EQ-5D-3L data from the Commonwealth Fund (CWF) Survey for Sick Adults ( n = 3958), comparing the standard error of the estimated mean utility in the CWF population using the predictive distribution from the Bayesian mixed-effect model (i.e., incorporating parameter uncertainty in the value set) with the standard error of the estimated mean utilities based on multiple imputation and the standard error using the conventional approach of using MAUI (i.e., ignoring uncertainty in the value set). The mean utility in the CWF population based on the predictive distribution of the Bayesian model was 0.827 with a standard error (SE) of 0.011. When utilities were derived using the conventional approach, the estimated mean utility was 0.827 with an SE of 0.003, which is only 25% of the SE based on the full predictive distribution of the mixed-effect model. Using multiple imputation with 20 imputed sets, the mean utility was 0.828 with an SE of 0.011, which is similar to the SE based on the full predictive distribution. Ignoring uncertainty of the predicted health utilities derived from MAUIs could lead to substantial underestimation of the variance of mean utilities. Multiple imputation corrects for this underestimation so that the results of cost-effectiveness analyses using MAUIs can report the correct degree of uncertainty.

Machine-learning techniques for fast and accurate feature localization in holograms of colloidal particles

NASA Astrophysics Data System (ADS)

Hannel, Mark D.; Abdulali, Aidan; O'Brien, Michael; Grier, David G.

2018-06-01

Holograms of colloidal particles can be analyzed with the Lorenz-Mie theory of light scattering to measure individual particles' three-dimensional positions with nanometer precision while simultaneously estimating their sizes and refractive indexes. Extracting this wealth of information begins by detecting and localizing features of interest within individual holograms. Conventionally approached with heuristic algorithms, this image analysis problem can be solved faster and more generally with machine-learning techniques. We demonstrate that two popular machine-learning algorithms, cascade classifiers and deep convolutional neural networks (CNN), can solve the feature-localization problem orders of magnitude faster than current state-of-the-art techniques. Our CNN implementation localizes holographic features precisely enough to bootstrap more detailed analyses based on the Lorenz-Mie theory of light scattering. The wavelet-based Haar cascade proves to be less precise, but is so computationally efficient that it creates new opportunities for applications that emphasize speed and low cost. We demonstrate its use as a real-time targeting system for holographic optical trapping.

Smartphone-Based Real-time Assessment of Swallowing Ability From the Swallowing Sound.

PubMed

Jayatilake, Dushyantha; Ueno, Tomoyuki; Teramoto, Yohei; Nakai, Kei; Hidaka, Kikue; Ayuzawa, Satoshi; Eguchi, Kiyoshi; Matsumura, Akira; Suzuki, Kenji

2015-01-01

Dysphagia can cause serious challenges to both physical and mental health. Aspiration due to dysphagia is a major health risk that could cause pneumonia and even death. The videofluoroscopic swallow study (VFSS), which is considered the gold standard for the diagnosis of dysphagia, is not widely available, expensive and causes exposure to radiation. The screening tests used for dysphagia need to be carried out by trained staff, and the evaluations are usually non-quantifiable. This paper investigates the development of the Swallowscope, a smartphone-based device and a feasible real-time swallowing sound-processing algorithm for the automatic screening, quantitative evaluation, and the visualisation of swallowing ability. The device can be used during activities of daily life with minimal intervention, making it potentially more capable of capturing aspirations and risky swallow patterns through the continuous monitoring. It also consists of a cloud-based system for the server-side analyzing and automatic sharing of the swallowing sound. The real-time algorithm we developed for the detection of dry and water swallows is based on a template matching approach. We analyzed the wavelet transformation-based spectral characteristics and the temporal characteristics of simultaneous synchronised VFSS and swallowing sound recordings of 25% barium mixed 3-ml water swallows of 70 subjects and the dry or saliva swallowing sound of 15 healthy subjects to establish the parameters of the template. With this algorithm, we achieved an overall detection accuracy of 79.3% (standard error: 4.2%) for the 92 water swallows; and a precision of 83.7% (range: 66.6%-100%) and a recall of 93.9% (range: 72.7%-100%) for the 71 episodes of dry swallows.

Smartphone-Based Real-time Assessment of Swallowing Ability From the Swallowing Sound

PubMed Central

Ueno, Tomoyuki; Teramoto, Yohei; Nakai, Kei; Hidaka, Kikue; Ayuzawa, Satoshi; Eguchi, Kiyoshi; Matsumura, Akira; Suzuki, Kenji

2015-01-01

Dysphagia can cause serious challenges to both physical and mental health. Aspiration due to dysphagia is a major health risk that could cause pneumonia and even death. The videofluoroscopic swallow study (VFSS), which is considered the gold standard for the diagnosis of dysphagia, is not widely available, expensive and causes exposure to radiation. The screening tests used for dysphagia need to be carried out by trained staff, and the evaluations are usually non-quantifiable. This paper investigates the development of the Swallowscope, a smartphone-based device and a feasible real-time swallowing sound-processing algorithm for the automatic screening, quantitative evaluation, and the visualisation of swallowing ability. The device can be used during activities of daily life with minimal intervention, making it potentially more capable of capturing aspirations and risky swallow patterns through the continuous monitoring. It also consists of a cloud-based system for the server-side analyzing and automatic sharing of the swallowing sound. The real-time algorithm we developed for the detection of dry and water swallows is based on a template matching approach. We analyzed the wavelet transformation-based spectral characteristics and the temporal characteristics of simultaneous synchronised VFSS and swallowing sound recordings of 25% barium mixed 3-ml water swallows of 70 subjects and the dry or saliva swallowing sound of 15 healthy subjects to establish the parameters of the template. With this algorithm, we achieved an overall detection accuracy of 79.3% (standard error: 4.2%) for the 92 water swallows; and a precision of 83.7% (range: 66.6%–100%) and a recall of 93.9% (range: 72.7%–100%) for the 71 episodes of dry swallows. PMID:27170905

Developpement de techniques numeriques pour l'estimation, la modelisation et la prediction de proprietes thermodynamiques et structurales de systems metalliques a fort ordonnancement chimique

NASA Astrophysics Data System (ADS)

Harvey, Jean-Philippe

In this work, the possibility to calculate and evaluate with a high degree of precision the Gibbs energy of complex multiphase equilibria for which chemical ordering is explicitly and simultaneously considered in the thermodynamic description of solid (short range order and long range order) and liquid (short range order) metallic phases is studied. The cluster site approximation (CSA) and the cluster variation method (CVM) are implemented in a new minimization technique of the Gibbs energy of multicomponent and multiphase systems to describe the thermodynamic behaviour of metallic solid solutions showing strong chemical ordering. The modified quasichemical model in the pair approximation (MQMPA) is also implemented in the new minimization algorithm presented in this work to describe the thermodynamic behaviour of metallic liquid solutions. The constrained minimization technique implemented in this work consists of a sequential quadratic programming technique based on an exact Newton’s method (i.e. the use of exact second derivatives in the determination of the Hessian of the objective function) combined to a line search method to identify a direction of sufficient decrease of the merit function. The implementation of a new algorithm to perform the constrained minimization of the Gibbs energy is justified by the difficulty to identify, in specific cases, the correct multiphase assemblage of a system where the thermodynamic behaviour of the equilibrium phases is described by one of the previously quoted models using the FactSage software (ex.: solid_CSA+liquid_MQMPA; solid1_CSA+solid2_CSA). After a rigorous validation of the constrained Gibbs energy minimization algorithm using several assessed binary and ternary systems found in the literature, the CVM and the CSA models used to describe the energetic behaviour of metallic solid solutions present in systems with key industrial applications such as the Cu-Zr and the Al-Zr systems are parameterized using fully consistent thermodynamic an structural data generated from a Monte Carlo (MC) simulator also implemented in the framework of this project. In this MC simulator, the modified embedded atom model in the second nearest neighbour formalism (MEAM-2NN) is used to describe the cohesive energy of each studied structure. A new Al-Zr MEAM-2NN interatomic potential needed to evaluate the cohesive energy of the condensed phases of this system is presented in this work. The thermodynamic integration (TI) method implemented in the MC simulator allows the evaluation of the absolute Gibbs energy of the considered solid or liquid structures. The original implementation of the TI method allowed us to evaluate theoretically for the first time all the thermodynamic mixing contributions (i.e., mixing enthalpy and mixing entropy contributions) of a metallic liquid (Cu-Zr and Al-Zr) and of a solid solution (face-centered cubic (FCC) Al-Zr solid solution) described by the MEAM-2NN. Thermodynamic and structural data obtained from MC and molecular dynamic simulations are then used to parameterize the CVM for the Al-Zr FCC solid solution and the MQMPA for the Al-Zr and the Cu-Zr liquid phase respectively. The extended thermodynamic study of these systems allow the introduction of a new type of configuration-dependent excess parameters in the definition of the thermodynamic function of solid solutions described by the CVM or the CSA. These parameters greatly improve the precision of these thermodynamic models based on experimental evidences found in the literature. A new parameterization approach of the MQMPA model of metallic liquid solutions is presented throughout this work. In this new approach, calculated pair fractions obtained from MC/MD simulations are taken into account as well as configuration-independent volumetric relaxation effects (regular like excess parameters) in order to parameterize precisely the Gibbs energy function of metallic melts. The generation of a complete set of fully consistent thermodynamic, physical and structural data for solid, liquid, and stoichiometric compounds and the subsequent parameterization of their respective thermodynamic model lead to the first description of the complete Al-Zr phase diagram in the range of composition [0 ≤ XZr ≤ 5 / 9] based on theoretical and fully consistent thermodynamic properties. MC and MD simulations are performed for the Al-Zr system to define for the first time the precise thermodynamic behaviour of the amorphous phase for its entire range of composition. Finally, all the thermodynamic models for the liquid phase, the FCC solid solution and the amorphous phase are used to define conditions based on thermodynamic and volumetric considerations that favor the amorphization of Al-Zr alloys.

MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design

DOE PAGES

Graf, Peter A.; Billups, Stephen

2017-07-24

Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles insteadmore » of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.« less

MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graf, Peter A.; Billups, Stephen

Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles insteadmore » of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.« less

A climatology of weather-driven mixing events in a dimictic Arctic lake

NASA Astrophysics Data System (ADS)

Cooke, Melanie; MacIntyre, Sally; Kushner, Paul

2014-05-01

For dimictic and polymictic Arctic lakes, mixing during the ice-free season is primarily controlled by the passage of cold fronts and their associated strong winds. At Toolik Lake, a Long Term Ecological Research site in Alaska, year-to-year variability in lake stability and mixing frequency has been considerable over the past 14 summers. Mixing is important for lake productivity, distributing dissolved gases and nutrients through the water column. Summertime Arctic warming might be expected to stabilize Arctic lakes such as Toolik, but the control of individual weather events on a season's mixing characteristics complicates the ability to predict trends in stability and mixing. With this motivation, this work aims to characterize weather systems that are conducive to mixing at Toolik. High resolution lake and meteorological data from the site were used to characterize mixing while atmospheric reanalysis data were used to describe the weather systems. Mixing events were first identified using an automated algorithm based on Lake Number and lake thermal structure. The algorithm identified mixing events that are separated by at least the timescale of weather systems, so that any given weather event should cause at most one mixing event. Because low Lake Number conditions typically highlight strong wind events, temperature profile data over time were used to identify thermocline deepening as a complementary indicator for mixing. Mixing events were found to be most often characterized by simultaneous occurrence of a low Lake Number condition and thermocline deepening. Once mixing events were identified, they were classified according to their corresponding atmospheric structures. Two primary weather system types with distinct characteristics were determined to be associated with mixing. The analysis suggests that changing the occurrence of these weather system types might change the summertime thermal structure of Toolik Lake, and by extension other lakes in the region.

Ceric and ferrous dosimeters show precision for 50-5000 rad range

NASA Technical Reports Server (NTRS)

Frigerio, N. A.; Henry, V. D.

1968-01-01

Ammonium thiocyanate, added to the usual ferrous sulfate dosimeter solution, yielded a very stable, precise and temperature-independent system eight times as sensitive as the classical Fricke system in the 50 to 5000 rad range. The ceric dosimeters, promising for use in mixed radiation fields, respond nearly independently of LET.

Robotic fish tracking method based on suboptimal interval Kalman filter

NASA Astrophysics Data System (ADS)

Tong, Xiaohong; Tang, Chao

2017-11-01

Autonomous Underwater Vehicle (AUV) research focused on tracking and positioning, precise guidance and return to dock and other fields. The robotic fish of AUV has become a hot application in intelligent education, civil and military etc. In nonlinear tracking analysis of robotic fish, which was found that the interval Kalman filter algorithm contains all possible filter results, but the range is wide, relatively conservative, and the interval data vector is uncertain before implementation. This paper proposes a ptimization algorithm of suboptimal interval Kalman filter. Suboptimal interval Kalman filter scheme used the interval inverse matrix with its worst inverse instead, is more approximate nonlinear state equation and measurement equation than the standard interval Kalman filter, increases the accuracy of the nominal dynamic system model, improves the speed and precision of tracking system. Monte-Carlo simulation results show that the optimal trajectory of sub optimal interval Kalman filter algorithm is better than that of the interval Kalman filter method and the standard method of the filter.

Improvements in Space Surveillance Processing for Wide Field of View Optical Sensors

NASA Astrophysics Data System (ADS)

Sydney, P.; Wetterer, C.

2014-09-01

For more than a decade, an autonomous satellite tracking system at the Air Force Maui Optical and Supercomputing (AMOS) observatory has been generating routine astrometric measurements of Earth-orbiting Resident Space Objects (RSOs) using small commercial telescopes and sensors. Recent work has focused on developing an improved processing system, enhancing measurement performance and response while supporting other sensor systems and missions. This paper will outline improved techniques in scheduling, detection, astrometric and photometric measurements, and catalog maintenance. The processing system now integrates with Special Perturbation (SP) based astrodynamics algorithms, allowing covariance-based scheduling and more precise orbital estimates and object identification. A merit-based scheduling algorithm provides a global optimization framework to support diverse collection tasks and missions. The detection algorithms support a range of target tracking and camera acquisition rates. New comprehensive star catalogs allow for more precise astrometric and photometric calibrations including differential photometry for monitoring environmental changes. This paper will also examine measurement performance with varying tracking rates and acquisition parameters.

Gated Sensor Fusion: A way to Improve the Precision of Ambulatory Human Body Motion Estimation.

PubMed

Olivares, Alberto; Górriz, J M; Ramírez, J; Olivares, Gonzalo

2014-01-01

Human body motion is usually variable in terms of intensity and, therefore, any Inertial Measurement Unit attached to a subject will measure both low and high angular rate and accelerations. This can be a problem for the accuracy of orientation estimation algorithms based on adaptive filters such as the Kalman filter, since both the variances of the process noise and the measurement noise are set at the beginning of the algorithm and remain constant during its execution. Setting fixed noise parameters burdens the adaptation capability of the filter if the intensity of the motion changes rapidly. In this work we present a conjoint novel algorithm which uses a motion intensity detector to dynamically vary the noise statistical parameters of different approaches of the Kalman filter. Results show that the precision of the estimated orientation in terms of the RMSE can be improved up to 29% with respect to the standard fixed-parameters approaches.

Machine-Learning Algorithms to Code Public Health Spending Accounts

PubMed Central

Leider, Jonathon P.; Resnick, Beth A.; Alfonso, Y. Natalia; Bishai, David

2017-01-01

Objectives: Government public health expenditure data sets require time- and labor-intensive manipulation to summarize results that public health policy makers can use. Our objective was to compare the performances of machine-learning algorithms with manual classification of public health expenditures to determine if machines could provide a faster, cheaper alternative to manual classification. Methods: We used machine-learning algorithms to replicate the process of manually classifying state public health expenditures, using the standardized public health spending categories from the Foundational Public Health Services model and a large data set from the US Census Bureau. We obtained a data set of 1.9 million individual expenditure items from 2000 to 2013. We collapsed these data into 147 280 summary expenditure records, and we followed a standardized method of manually classifying each expenditure record as public health, maybe public health, or not public health. We then trained 9 machine-learning algorithms to replicate the manual process. We calculated recall, precision, and coverage rates to measure the performance of individual and ensembled algorithms. Results: Compared with manual classification, the machine-learning random forests algorithm produced 84% recall and 91% precision. With algorithm ensembling, we achieved our target criterion of 90% recall by using a consensus ensemble of ≥6 algorithms while still retaining 93% coverage, leaving only 7% of the summary expenditure records unclassified. Conclusions: Machine learning can be a time- and cost-saving tool for estimating public health spending in the United States. It can be used with standardized public health spending categories based on the Foundational Public Health Services model to help parse public health expenditure information from other types of health-related spending, provide data that are more comparable across public health organizations, and evaluate the impact of evidence-based public health resource allocation. PMID:28363034

Machine-Learning Algorithms to Code Public Health Spending Accounts.

PubMed

Brady, Eoghan S; Leider, Jonathon P; Resnick, Beth A; Alfonso, Y Natalia; Bishai, David

Government public health expenditure data sets require time- and labor-intensive manipulation to summarize results that public health policy makers can use. Our objective was to compare the performances of machine-learning algorithms with manual classification of public health expenditures to determine if machines could provide a faster, cheaper alternative to manual classification. We used machine-learning algorithms to replicate the process of manually classifying state public health expenditures, using the standardized public health spending categories from the Foundational Public Health Services model and a large data set from the US Census Bureau. We obtained a data set of 1.9 million individual expenditure items from 2000 to 2013. We collapsed these data into 147 280 summary expenditure records, and we followed a standardized method of manually classifying each expenditure record as public health, maybe public health, or not public health. We then trained 9 machine-learning algorithms to replicate the manual process. We calculated recall, precision, and coverage rates to measure the performance of individual and ensembled algorithms. Compared with manual classification, the machine-learning random forests algorithm produced 84% recall and 91% precision. With algorithm ensembling, we achieved our target criterion of 90% recall by using a consensus ensemble of ≥6 algorithms while still retaining 93% coverage, leaving only 7% of the summary expenditure records unclassified. Machine learning can be a time- and cost-saving tool for estimating public health spending in the United States. It can be used with standardized public health spending categories based on the Foundational Public Health Services model to help parse public health expenditure information from other types of health-related spending, provide data that are more comparable across public health organizations, and evaluate the impact of evidence-based public health resource allocation.

Automated identification of drug and food allergies entered using non-standard terminology.

PubMed

Epstein, Richard H; St Jacques, Paul; Stockin, Michael; Rothman, Brian; Ehrenfeld, Jesse M; Denny, Joshua C

2013-01-01

An accurate computable representation of food and drug allergy is essential for safe healthcare. Our goal was to develop a high-performance, easily maintained algorithm to identify medication and food allergies and sensitivities from unstructured allergy entries in electronic health record (EHR) systems. An algorithm was developed in Transact-SQL to identify ingredients to which patients had allergies in a perioperative information management system. The algorithm used RxNorm and natural language processing techniques developed on a training set of 24 599 entries from 9445 records. Accuracy, specificity, precision, recall, and F-measure were determined for the training dataset and repeated for the testing dataset (24 857 entries from 9430 records). Accuracy, precision, recall, and F-measure for medication allergy matches were all above 98% in the training dataset and above 97% in the testing dataset for all allergy entries. Corresponding values for food allergy matches were above 97% and above 93%, respectively. Specificities of the algorithm were 90.3% and 85.0% for drug matches and 100% and 88.9% for food matches in the training and testing datasets, respectively. The algorithm had high performance for identification of medication and food allergies. Maintenance is practical, as updates are managed through upload of new RxNorm versions and additions to companion database tables. However, direct entry of codified allergy information by providers (through autocompleters or drop lists) is still preferred to post-hoc encoding of the data. Data tables used in the algorithm are available for download. A high performing, easily maintained algorithm can successfully identify medication and food allergies from free text entries in EHR systems.

Autonomous Precision Landing and Hazard Avoidance Technology (ALHAT) Project Status as of May 2010

NASA Technical Reports Server (NTRS)

Striepe, Scott A.; Epp, Chirold D.; Robertson, Edward A.

2010-01-01

This paper includes the current status of NASA s Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) Project. The ALHAT team has completed several flight tests and two major design analysis cycles. These tests and analyses examine terrain relative navigation sensors, hazard detection and avoidance sensors and algorithms, and hazard relative navigation algorithms, and the guidance and navigation system using these ALHAT functions. The next flight test is scheduled for July 2010. The paper contains results from completed flight tests and analysis cycles. ALHAT system status, upcoming tests and analyses is also addressed. The current ALHAT plans as of May 2010 are discussed. Application of the ALHAT system to landing on bodies other than the Moon is included

A compression scheme for radio data in high performance computing

NASA Astrophysics Data System (ADS)

Masui, K.; Amiri, M.; Connor, L.; Deng, M.; Fandino, M.; Höfer, C.; Halpern, M.; Hanna, D.; Hincks, A. D.; Hinshaw, G.; Parra, J. M.; Newburgh, L. B.; Shaw, J. R.; Vanderlinde, K.

2015-09-01

We present a procedure for efficiently compressing astronomical radio data for high performance applications. Integrated, post-correlation data are first passed through a nearly lossless rounding step which compares the precision of the data to a generalized and calibration-independent form of the radiometer equation. This allows the precision of the data to be reduced in a way that has an insignificant impact on the data. The newly developed Bitshuffle lossless compression algorithm is subsequently applied. When the algorithm is used in conjunction with the HDF5 library and data format, data produced by the CHIME Pathfinder telescope is compressed to 28% of its original size and decompression throughputs in excess of 1 GB/s are obtained on a single core.

Mixed Criticality Scheduling for Industrial Wireless Sensor Networks

PubMed Central

Jin, Xi; Xia, Changqing; Xu, Huiting; Wang, Jintao; Zeng, Peng

2016-01-01

Wireless sensor networks (WSNs) have been widely used in industrial systems. Their real-time performance and reliability are fundamental to industrial production. Many works have studied the two aspects, but only focus on single criticality WSNs. Mixed criticality requirements exist in many advanced applications in which different data flows have different levels of importance (or criticality). In this paper, first, we propose a scheduling algorithm, which guarantees the real-time performance and reliability requirements of data flows with different levels of criticality. The algorithm supports centralized optimization and adaptive adjustment. It is able to improve both the scheduling performance and flexibility. Then, we provide the schedulability test through rigorous theoretical analysis. We conduct extensive simulations, and the results demonstrate that the proposed scheduling algorithm and analysis significantly outperform existing ones. PMID:27589741

Intra-organizational Computation and Complexity

DTIC Science & Technology

2003-01-01

models. New methodologies, centered on understanding algorithmic complexity, are being developed that may enable us to better handle network data ...tractability of data analysis, and enable more precise theorization. A variety of measures of algorithmic complexity, e.g., Kolmogorov-Chaitin, and a...variety of proxies exist (which are often turned to for pragmatic reasons) ( Lempel and Ziv ,1976). For the most part, social and organizational

Exponentially more precise quantum simulation of fermions in the configuration interaction representation

NASA Astrophysics Data System (ADS)

Babbush, Ryan; Berry, Dominic W.; Sanders, Yuval R.; Kivlichan, Ian D.; Scherer, Artur; Wei, Annie Y.; Love, Peter J.; Aspuru-Guzik, Alán

2018-01-01

We present a quantum algorithm for the simulation of molecular systems that is asymptotically more efficient than all previous algorithms in the literature in terms of the main problem parameters. As in Babbush et al (2016 New Journal of Physics 18, 033032), we employ a recently developed technique for simulating Hamiltonian evolution using a truncated Taylor series to obtain logarithmic scaling with the inverse of the desired precision. The algorithm of this paper involves simulation under an oracle for the sparse, first-quantized representation of the molecular Hamiltonian known as the configuration interaction (CI) matrix. We construct and query the CI matrix oracle to allow for on-the-fly computation of molecular integrals in a way that is exponentially more efficient than classical numerical methods. Whereas second-quantized representations of the wavefunction require \\widetilde{{ O }}(N) qubits, where N is the number of single-particle spin-orbitals, the CI matrix representation requires \\widetilde{{ O }}(η ) qubits, where η \\ll N is the number of electrons in the molecule of interest. We show that the gate count of our algorithm scales at most as \\widetilde{{ O }}({η }2{N}3t).

An adaptive compensation algorithm for temperature drift of micro-electro-mechanical systems gyroscopes using a strong tracking Kalman filter.

PubMed

Feng, Yibo; Li, Xisheng; Zhang, Xiaojuan

2015-05-13

We present an adaptive algorithm for a system integrated with micro-electro-mechanical systems (MEMS) gyroscopes and a compass to eliminate the influence from the environment, compensate the temperature drift precisely, and improve the accuracy of the MEMS gyroscope. We use a simplified drift model and changing but appropriate model parameters to implement this algorithm. The model of MEMS gyroscope temperature drift is constructed mostly on the basis of the temperature sensitivity of the gyroscope. As the state variables of a strong tracking Kalman filter (STKF), the parameters of the temperature drift model can be calculated to adapt to the environment under the support of the compass. These parameters change intelligently with the environment to maintain the precision of the MEMS gyroscope in the changing temperature. The heading error is less than 0.6° in the static temperature experiment, and also is kept in the range from 5° to -2° in the dynamic outdoor experiment. This demonstrates that the proposed algorithm exhibits strong adaptability to a changing temperature, and performs significantly better than KF and MLR to compensate the temperature drift of a gyroscope and eliminate the influence of temperature variation.

A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM.

PubMed

Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei; Song, Houbing

2018-01-15

Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model's performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM's parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models' performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors.

BIG DATA ANALYTICS AND PRECISION ANIMAL AGRICULTURE SYMPOSIUM: Data to decisions.

PubMed

White, B J; Amrine, D E; Larson, R L

2018-04-14

Big data are frequently used in many facets of business and agronomy to enhance knowledge needed to improve operational decisions. Livestock operations collect data of sufficient quantity to perform predictive analytics. Predictive analytics can be defined as a methodology and suite of data evaluation techniques to generate a prediction for specific target outcomes. The objective of this manuscript is to describe the process of using big data and the predictive analytic framework to create tools to drive decisions in livestock production, health, and welfare. The predictive analytic process involves selecting a target variable, managing the data, partitioning the data, then creating algorithms, refining algorithms, and finally comparing accuracy of the created classifiers. The partitioning of the datasets allows model building and refining to occur prior to testing the predictive accuracy of the model with naive data to evaluate overall accuracy. Many different classification algorithms are available for predictive use and testing multiple algorithms can lead to optimal results. Application of a systematic process for predictive analytics using data that is currently collected or that could be collected on livestock operations will facilitate precision animal management through enhanced livestock operational decisions.

Spacecraft Attitude Tracking and Maneuver Using Combined Magnetic Actuators

NASA Technical Reports Server (NTRS)

Zhou, Zhiqiang

2010-01-01

The accuracy of spacecraft attitude control using magnetic actuators only is low and on the order of 0.4-5 degrees. The key reason is that the magnetic torque is two-dimensional and it is only in the plane perpendicular to the magnetic field vector. In this paper novel attitude control algorithms using the combination of magnetic actuators with Reaction Wheel Assembles (RWAs) or other types of actuators, such as thrusters, are presented. The combination of magnetic actuators with one or two RWAs aligned with different body axis expands the two-dimensional control torque to three-dimensional. The algorithms can guarantee the spacecraft attitude and rates to track the commanded attitude precisely. A design example is presented for Nadir pointing, pitch and yaw maneuvers. The results show that precise attitude tracking can be reached and the attitude control accuracy is comparable with RWAs based attitude control. The algorithms are also useful for the RWAs based attitude control. When there are only one or two workable RWAs due to RWA failures, the attitude control system can switch to the control algorithms for the combined magnetic actuators with the RWAs without going to the safe mode and the control accuracy can be maintained.

Randomized controlled clinical trial on the three-dimensional accuracy of fast-set impression materials.

PubMed

Rudolph, Heike; Quaas, Sebastian; Haim, Manuela; Preißler, Jörg; Walter, Michael H; Koch, Rainer; Luthardt, Ralph G

2013-06-01

The use of fast-setting impression materials with different viscosities for the one-stage impression technique demands precise working times when mixing. We examined the effect of varying working time on impression precision in a randomized clinical trial. Focusing on tooth 46, three impressions were made from each of 96 volunteers, using either a polyether (PE: Impregum Penta H/L DuoSoft Quick, 3 M ESPE) or an addition-curing silicone (AS: Aquasil Ultra LV, Dentsply/DeTrey), one with the manufacturer's recommended working time (used as a reference) and two with altered working times. All stages of the impression-taking were subject to randomization. The three-dimensional precision of the non-standard working time impressions was digitally analyzed compared to the reference impression. Statistical analysis was performed using multivariate models. The mean difference in the position of the lower right first molar (vs. the reference impression) ranged from ±12 μm for PE to +19 and -14 μm for AS. Significantly higher mean values (+62 to -40 μm) were found for AS compared to PE (+21 to -26 μm) in the area of the distal adjacent tooth. Fast-set impression materials offer high precision when used for single tooth restorations as part of a one-stage impression technique, even when the working time (mixing plus application of the light- and heavy-body components) diverges significantly from the manufacturer's recommended protocol. Best accuracy was achieved with machine-mixed heavy-body/light-body polyether. Both materials examined met the clinical requirements regarding precision when the teeth were completely syringed with light material.

Precision half-life measurement of 17F

NASA Astrophysics Data System (ADS)

Brodeur, M.; Nicoloff, C.; Ahn, T.; Allen, J.; Bardayan, D. W.; Becchetti, F. D.; Gupta, Y. K.; Hall, M. R.; Hall, O.; Hu, J.; Kelly, J. M.; Kolata, J. J.; Long, J.; O'Malley, P.; Schultz, B. E.

2016-02-01

Background: The precise determination of f t values for superallowed mixed transitions between mirror nuclide are gaining attention as they could provide an avenue to test the theoretical corrections used to extract the Vu d matrix element from superallowed pure Fermi transitions. The 17F decay is particularly interesting as it proceeds completely to the ground state of 17O, removing the need for branching ratio measurements. The dominant uncertainty on the f t value of the 17F mirror transition stems from a number of conflicting half-life measurements. Purpose: A precision half-life measurement of 17F was performed and compared to previous results. Methods: The life-time was determined from the β counting of implanted 17F on a Ta foil that was removed from the beam for counting. The 17F beam was produced by transfers reaction and separated by the TwinSol facility of the Nuclear Science Laboratory of the University of Notre Dame. Results: The measured value of t1/2 new=64.402 (42) s is in agreement with several past measurements and represents one of the most precise measurements to date. In anticipation of future measurements of the correlation parameters for the decay and using the new world average t1/2 world=64.398 (61) s, we present a new estimate of the mixing ratio ρ for the mixed transition as well as the correlation parameters based on assuming Standard Model validity. Conclusions: The relative uncertainty on the new world average for the half-life is dominated by the large χ2=31 of the existing measurements. More precision measurements with different systematics are needed to remedy to the situation.

Test Generation Algorithm for Fault Detection of Analog Circuits Based on Extreme Learning Machine

PubMed Central

Zhou, Jingyu; Tian, Shulin; Yang, Chenglin; Ren, Xuelong

2014-01-01

This paper proposes a novel test generation algorithm based on extreme learning machine (ELM), and such algorithm is cost-effective and low-risk for analog device under test (DUT). This method uses test patterns derived from the test generation algorithm to stimulate DUT, and then samples output responses of the DUT for fault classification and detection. The novel ELM-based test generation algorithm proposed in this paper contains mainly three aspects of innovation. Firstly, this algorithm saves time efficiently by classifying response space with ELM. Secondly, this algorithm can avoid reduced test precision efficiently in case of reduction of the number of impulse-response samples. Thirdly, a new process of test signal generator and a test structure in test generation algorithm are presented, and both of them are very simple. Finally, the abovementioned improvement and functioning are confirmed in experiments. PMID:25610458

A polarized low-coherence interferometry demodulation algorithm by recovering the absolute phase of a selected monochromatic frequency.

PubMed

Jiang, Junfeng; Wang, Shaohua; Liu, Tiegen; Liu, Kun; Yin, Jinde; Meng, Xiange; Zhang, Yimo; Wang, Shuang; Qin, Zunqi; Wu, Fan; Li, Dingjie

2012-07-30

A demodulation algorithm based on absolute phase recovery of a selected monochromatic frequency is proposed for optical fiber Fabry-Perot pressure sensing system. The algorithm uses Fourier transform to get the relative phase and intercept of the unwrapped phase-frequency linear fit curve to identify its interference-order, which are then used to recover the absolute phase. A simplified mathematical model of the polarized low-coherence interference fringes was established to illustrate the principle of the proposed algorithm. Phase unwrapping and the selection of monochromatic frequency were discussed in detail. Pressure measurement experiment was carried out to verify the effectiveness of the proposed algorithm. Results showed that the demodulation precision by our algorithm could reach up to 0.15kPa, which has been improved by 13 times comparing with phase slope based algorithm.

A Modularity-Based Method Reveals Mixed Modules from Chemical-Gene Heterogeneous Network

PubMed Central

Song, Jianglong; Tang, Shihuan; Liu, Xi; Gao, Yibo; Yang, Hongjun; Lu, Peng

2015-01-01

For a multicomponent therapy, molecular network is essential to uncover its specific mode of action from a holistic perspective. The molecular system of a Traditional Chinese Medicine (TCM) formula can be represented by a 2-class heterogeneous network (2-HN), which typically includes chemical similarities, chemical-target interactions and gene interactions. An important premise of uncovering the molecular mechanism is to identify mixed modules from complex chemical-gene heterogeneous network of a TCM formula. We thus proposed a novel method (MixMod) based on mixed modularity to detect accurate mixed modules from 2-HNs. At first, we compared MixMod with Clauset-Newman-Moore algorithm (CNM), Markov Cluster algorithm (MCL), Infomap and Louvain on benchmark 2-HNs with known module structure. Results showed that MixMod was superior to other methods when 2-HNs had promiscuous module structure. Then these methods were tested on a real drug-target network, in which 88 disease clusters were regarded as real modules. MixMod could identify the most accurate mixed modules from the drug-target 2-HN (normalized mutual information 0.62 and classification accuracy 0.4524). In the end, MixMod was applied to the 2-HN of Buchang naoxintong capsule (BNC) and detected 49 mixed modules. By using enrichment analysis, we investigated five mixed modules that contained primary constituents of BNC intestinal absorption liquid. As a matter of fact, the findings of in vitro experiments using BNC intestinal absorption liquid were found to highly accord with previous analysis. Therefore, MixMod is an effective method to detect accurate mixed modules from chemical-gene heterogeneous networks and further uncover the molecular mechanism of multicomponent therapies, especially TCM formulae. PMID:25927435

Mixed time integration methods for transient thermal analysis of structures, appendix 5

NASA Technical Reports Server (NTRS)

Liu, W. K.

1982-01-01

Mixed time integration methods for transient thermal analysis of structures are studied. An efficient solution procedure for predicting the thermal behavior of aerospace vehicle structures was developed. A 2D finite element computer program incorporating these methodologies is being implemented. The performance of these mixed time finite element algorithms can then be evaluated employing the proposed example problem.

The Comparison Between Nmf and Ica in Pigment Mixture Identification of Ancient Chinese Paintings

NASA Astrophysics Data System (ADS)

Liu, Y.; Lyu, S.; Hou, M.; Yin, Q.

2018-04-01

Since the colour in painting cultural relics observed by our naked eyes or hyperspectral cameras is usually a mixture of several kinds of pigments, the mixed pigments analysis will be an important subject in the field of ancient painting conservation and restoration. This paper aims to find a more effective method to confirm the types of every pure pigment from mixture on the surface of paintings. Firstly, we adopted two kinds of blind source separation algorithms, which are independent component analysis and non-negative matrix factorization, to extract the pure pigment component from mixed spectrum respectively. Moreover, we matched the separated pure spectrum with the pigments spectra library built by our team to determine the pigment type. Furthermore, three kinds of data including simulation data, mixed pigments spectral data measured in laboratory, and the spectral data of an ancient painting were chosen to evaluate the performance of the different algorithms. And the accuracy was compared between the two algorithms. Finally, the experimental results show that non-negative matrix factorization method is more suitable for endmember extraction in the field of ancient painting conservation and restoration.

High-Performance Mixed Models Based Genome-Wide Association Analysis with omicABEL software

PubMed Central

Fabregat-Traver, Diego; Sharapov, Sodbo Zh.; Hayward, Caroline; Rudan, Igor; Campbell, Harry; Aulchenko, Yurii; Bientinesi, Paolo

2014-01-01

To raise the power of genome-wide association studies (GWAS) and avoid false-positive results in structured populations, one can rely on mixed model based tests. When large samples are used, and when multiple traits are to be studied in the ’omics’ context, this approach becomes computationally challenging. Here we consider the problem of mixed-model based GWAS for arbitrary number of traits, and demonstrate that for the analysis of single-trait and multiple-trait scenarios different computational algorithms are optimal. We implement these optimal algorithms in a high-performance computing framework that uses state-of-the-art linear algebra kernels, incorporates optimizations, and avoids redundant computations, increasing throughput while reducing memory usage and energy consumption. We show that, compared to existing libraries, our algorithms and software achieve considerable speed-ups. The OmicABEL software described in this manuscript is available under the GNU GPL v. 3 license as part of the GenABEL project for statistical genomics at http: //www.genabel.org/packages/OmicABEL. PMID:25717363

High-Performance Mixed Models Based Genome-Wide Association Analysis with omicABEL software.

PubMed

Fabregat-Traver, Diego; Sharapov, Sodbo Zh; Hayward, Caroline; Rudan, Igor; Campbell, Harry; Aulchenko, Yurii; Bientinesi, Paolo

2014-01-01

To raise the power of genome-wide association studies (GWAS) and avoid false-positive results in structured populations, one can rely on mixed model based tests. When large samples are used, and when multiple traits are to be studied in the 'omics' context, this approach becomes computationally challenging. Here we consider the problem of mixed-model based GWAS for arbitrary number of traits, and demonstrate that for the analysis of single-trait and multiple-trait scenarios different computational algorithms are optimal. We implement these optimal algorithms in a high-performance computing framework that uses state-of-the-art linear algebra kernels, incorporates optimizations, and avoids redundant computations, increasing throughput while reducing memory usage and energy consumption. We show that, compared to existing libraries, our algorithms and software achieve considerable speed-ups. The OmicABEL software described in this manuscript is available under the GNU GPL v. 3 license as part of the GenABEL project for statistical genomics at http: //www.genabel.org/packages/OmicABEL.

Modeling and Positioning of a PZT Precision Drive System.

PubMed

Liu, Che; Guo, Yanling

2017-11-08

The fact that piezoelectric ceramic transducer (PZT) precision drive systems in 3D printing are faced with nonlinear problems with respect to positioning, such as hysteresis and creep, has had an extremely negative impact on the precision of laser focusing systems. To eliminate the impact of PZT nonlinearity during precision drive movement, mathematical modeling and theoretical analyses of each module comprising the system were carried out in this study, a micro-displacement measurement circuit based on Position Sensitive Detector (PSD) is constructed, followed by the establishment of system closed-loop control and creep control models. An XL-80 laser interferometer (Renishaw, Wotton-under-Edge, UK) was used to measure the performance of the precision drive system, showing that system modeling and control algorithms were correct, with the requirements for precision positioning of the drive system satisfied.

Modeling and Positioning of a PZT Precision Drive System

PubMed Central

Liu, Che; Guo, Yanling

2017-01-01

The fact that piezoelectric ceramic transducer (PZT) precision drive systems in 3D printing are faced with nonlinear problems with respect to positioning, such as hysteresis and creep, has had an extremely negative impact on the precision of laser focusing systems. To eliminate the impact of PZT nonlinearity during precision drive movement, mathematical modeling and theoretical analyses of each module comprising the system were carried out in this study, a micro-displacement measurement circuit based on Position Sensitive Detector (PSD) is constructed, followed by the establishment of system closed-loop control and creep control models. An XL-80 laser interferometer (Renishaw, Wotton-under-Edge, UK) was used to measure the performance of the precision drive system, showing that system modeling and control algorithms were correct, with the requirements for precision positioning of the drive system satisfied. PMID:29117140

Measurement of the Effective Weak Mixing Angle in p p ¯ → Z / γ * → e + e - Events

DOE PAGES

Abazov, V.  M.; Abbott, B.; Acharya, B.  S.; ...

2015-07-22

We present a measurement of the fundamental parameter of the standard model, the weak mixing angle sin 2θ ℓ eff which determines the relative strength of weak and electromagnetic interactions, in pp¯→Z/γ*→e +e - events at a center of mass energy of 1.96 TeV, using data corresponding to 9.7 fb -1 of integrated luminosity collected by the D0 detector at the Fermilab Tevatron. The effective weak mixing angle is extracted from the forward-backward charge asymmetry as a function of the invariant mass around the Z boson pole. The measured value of sin 2θ ℓ eff=0.23147±0.00047 is the most precise measurementmore » from light quark interactions to date, with a precision close to the best LEP and SLD results.« less

Zooming in on neutrino oscillations with DUNE

NASA Astrophysics Data System (ADS)

Srivastava, Rahul; Ternes, Christoph A.; Tórtola, Mariam; Valle, José W. F.

2018-05-01

We examine the capabilities of the DUNE experiment as a probe of the neutrino mixing paradigm. Taking the current status of neutrino oscillations and the design specifications of DUNE, we determine the experiment's potential to probe the structure of neutrino mixing and C P violation. We focus on the poorly determined parameters θ23 and δC P and consider both two and seven years of run. We take various benchmarks as our true values, such as the current preferred values of θ23 and δC P, as well as several theory-motivated choices. We determine quantitatively DUNE's potential to perform a precision measurement of θ23, as well as to test the C P violation hypothesis in a model-independent way. We find that, after running for seven years, DUNE will make a substantial step in the precise determination of these parameters, bringing to quantitative test the predictions of various theories of neutrino mixing.

Measurement of the Effective Weak Mixing Angle in p p ¯ → Z / γ * → e + e - Events

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abazov, V. M.; Abbott, B.; Acharya, B. S.

2015-07-22

We present a measurement of the fundamental parameter of the standard model, the weak mixing angle sin 2θ ℓ eff which determines the relative strength of weak and electromagnetic interactions, in pp¯→Z/γ*→e +e - events at a center of mass energy of 1.96 TeV, using data corresponding to 9.7 fb -1 of integrated luminosity collected by the D0 detector at the Fermilab Tevatron. The effective weak mixing angle is extracted from the forward-backward charge asymmetry as a function of the invariant mass around the Z boson pole. The measured value of sin 2θ ℓ eff=0.23147±0.00047 is the most precise measurementmore » from light quark interactions to date, with a precision close to the best LEP and SLD results.« less

Development of a Field-Deployable Methane Carbon Isotope Analyzer

NASA Astrophysics Data System (ADS)

Dong, Feng; Baer, Douglas

2010-05-01

Methane is a potent greenhouse gas, whose atmospheric surface mixing ratio has almost doubled compared with preindustrial values. Methane can be produced by biogenic processes, thermogenic processes or biomass, with different isotopic signatures. As a key molecule involved in the radiative forcing in the atmosphere, methane is thus one of the most important molecules linking the biosphere and atmosphere. Therefore precise measurements of mixing ratios and isotopic compositions will help scientists to better understand methane sources and sinks. To date, high precision isotope measurements have been exclusively performed with conventional isotope ratio mass spectrometry, which involves intensive labor and is not readily field deployable. Optical studies using infrared laser spectroscopy have also been reported to measure the isotopic ratios. However, the precision of optical-based analyses, to date, is typically unsatisfactory without pre-concentration procedures. We present characterization of the performance of a portable Methane Carbon Isotope Analyzer (MCIA), based on cavity enhanced laser absorption spectroscopy technique, that provides in-situ measurements of the carbon isotope ratio (13C/12C or del_13C) and methane mixing ratio (CH4). The sample is introduced to the analyzer directly without any requirement for pretreatment or preconcentration. A typical precision of less than 1 per mill (< 0.1%) with a 10-ppm methane sample can be achieved in a measurement time of less than 100 seconds. The MCIA can report carbon isotope ratio and concentration measurements over a very wide range of methane concentrations. Results of laboratory tests and field measurements will be presented.

Correction algorithm for online continuous flow δ13C and δ18O carbonate and cellulose stable isotope analyses

NASA Astrophysics Data System (ADS)

Evans, M. N.; Selmer, K. J.; Breeden, B. T.; Lopatka, A. S.; Plummer, R. E.

2016-09-01

We describe an algorithm to correct for scale compression, runtime drift, and amplitude effects in carbonate and cellulose oxygen and carbon isotopic analyses made on two online continuous flow isotope ratio mass spectrometry (CF-IRMS) systems using gas chromatographic (GC) separation. We validate the algorithm by correcting measurements of samples of known isotopic composition which are not used to estimate the corrections. For carbonate δ13C (δ18O) data, median precision of validation estimates for two reference materials and two calibrated working standards is 0.05‰ (0.07‰); median bias is 0.04‰ (0.02‰) over a range of 49.2‰ (24.3‰). For α-cellulose δ13C (δ18O) data, median precision of validation estimates for one reference material and five working standards is 0.11‰ (0.27‰); median bias is 0.13‰ (-0.10‰) over a range of 16.1‰ (19.1‰). These results are within the 5th-95th percentile range of subsequent routine runtime validation exercises in which one working standard is used to calibrate the other. Analysis of the relative importance of correction steps suggests that drift and scale-compression corrections are most reliable and valuable. If validation precisions are not already small, routine cross-validated precision estimates are improved by up to 50% (80%). The results suggest that correction for systematic error may enable these particular CF-IRMS systems to produce δ13C and δ18O carbonate and cellulose isotopic analyses with higher validated precision, accuracy, and throughput than is typically reported for these systems. The correction scheme may be used in support of replication-intensive research projects in paleoclimatology and other data-intensive applications within the geosciences.

A mixed-mode traffic assignment model with new time-flow impedance function

NASA Astrophysics Data System (ADS)

Lin, Gui-Hua; Hu, Yu; Zou, Yuan-Yang

2018-01-01

Recently, with the wide adoption of electric vehicles, transportation network has shown different characteristics and been further developed. In this paper, we present a new time-flow impedance function, which may be more realistic than the existing time-flow impedance functions. Based on this new impedance function, we present an optimization model for a mixed-mode traffic network in which battery electric vehicles (BEVs) and gasoline vehicles (GVs) are chosen. We suggest two approaches to handle the model: One is to use the interior point (IP) algorithm and the other is to employ the sequential quadratic programming (SQP) algorithm. Three numerical examples are presented to illustrate the efficiency of these approaches. In particular, our numerical results show that more travelers prefer to choosing BEVs when the distance limit of BEVs is long enough and the unit operating cost of GVs is higher than that of BEVs, and the SQP algorithm is faster than the IP algorithm.

An unbiased risk estimator for image denoising in the presence of mixed poisson-gaussian noise.

PubMed

Le Montagner, Yoann; Angelini, Elsa D; Olivo-Marin, Jean-Christophe

2014-03-01

The behavior and performance of denoising algorithms are governed by one or several parameters, whose optimal settings depend on the content of the processed image and the characteristics of the noise, and are generally designed to minimize the mean squared error (MSE) between the denoised image returned by the algorithm and a virtual ground truth. In this paper, we introduce a new Poisson-Gaussian unbiased risk estimator (PG-URE) of the MSE applicable to a mixed Poisson-Gaussian noise model that unifies the widely used Gaussian and Poisson noise models in fluorescence bioimaging applications. We propose a stochastic methodology to evaluate this estimator in the case when little is known about the internal machinery of the considered denoising algorithm, and we analyze both theoretically and empirically the characteristics of the PG-URE estimator. Finally, we evaluate the PG-URE-driven parametrization for three standard denoising algorithms, with and without variance stabilizing transforms, and different characteristics of the Poisson-Gaussian noise mixture.

Prototype Mixed Finite Element Hydrodynamics Capability in ARES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rieben, R N

This document describes work on a prototype Mixed Finite Element Method (MFEM) hydrodynamics algorithm in the ARES code, and its application to a set of standard test problems. This work is motivated by the need for improvements to the algorithms used in the Lagrange hydrodynamics step to make them more robust. We begin by identifying the outstanding issues with traditional numerical hydrodynamics algorithms followed by a description of the proposed method and how it may address several of these longstanding issues. We give a theoretical overview of the proposed MFEM algorithm as well as a summary of the coding additionsmore » and modifications that were made to add this capability to the ARES code. We present results obtained with the new method on a set of canonical hydrodynamics test problems and demonstrate significant improvement in comparison to results obtained with traditional methods. We conclude with a summary of the issues still at hand and motivate the need for continued research to develop the proposed method into maturity.« less

Content-aware dark image enhancement through channel division.

PubMed

Rivera, Adin Ramirez; Ryu, Byungyong; Chae, Oksam

2012-09-01

The current contrast enhancement algorithms occasionally result in artifacts, overenhancement, and unnatural effects in the processed images. These drawbacks increase for images taken under poor illumination conditions. In this paper, we propose a content-aware algorithm that enhances dark images, sharpens edges, reveals details in textured regions, and preserves the smoothness of flat regions. The algorithm produces an ad hoc transformation for each image, adapting the mapping functions to each image's characteristics to produce the maximum enhancement. We analyze the contrast of the image in the boundary and textured regions, and group the information with common characteristics. These groups model the relations within the image, from which we extract the transformation functions. The results are then adaptively mixed, by considering the human vision system characteristics, to boost the details in the image. Results show that the algorithm can automatically process a wide range of images-e.g., mixed shadow and bright areas, outdoor and indoor lighting, and face images-without introducing artifacts, which is an improvement over many existing methods.

Variational optimization algorithms for uniform matrix product states

NASA Astrophysics Data System (ADS)

Zauner-Stauber, V.; Vanderstraeten, L.; Fishman, M. T.; Verstraete, F.; Haegeman, J.

2018-01-01

We combine the density matrix renormalization group (DMRG) with matrix product state tangent space concepts to construct a variational algorithm for finding ground states of one-dimensional quantum lattices in the thermodynamic limit. A careful comparison of this variational uniform matrix product state algorithm (VUMPS) with infinite density matrix renormalization group (IDMRG) and with infinite time evolving block decimation (ITEBD) reveals substantial gains in convergence speed and precision. We also demonstrate that VUMPS works very efficiently for Hamiltonians with long-range interactions and also for the simulation of two-dimensional models on infinite cylinders. The new algorithm can be conveniently implemented as an extension of an already existing DMRG implementation.

A maximally stable extremal region based scene text localization method

NASA Astrophysics Data System (ADS)

Xiao, Chengqiu; Ji, Lixin; Gao, Chao; Li, Shaomei

2015-07-01

Text localization in natural scene images is an important prerequisite for many content-based image analysis tasks. This paper proposes a novel text localization algorithm. Firstly, a fast pruning algorithm is designed to extract Maximally Stable Extremal Regions (MSER) as basic character candidates. Secondly, these candidates are filtered by using the properties of fitting ellipse and the distribution properties of characters to exclude most non-characters. Finally, a new extremal regions projection merging algorithm is designed to group character candidates into words. Experimental results show that the proposed method has an advantage in speed and achieve relatively high precision and recall rates than the latest published algorithms.

Advanced Targeting Cost Function Design for Evolutionary Optimization of Control of Logistic Equation

NASA Astrophysics Data System (ADS)

Senkerik, Roman; Zelinka, Ivan; Davendra, Donald; Oplatkova, Zuzana

2010-06-01

This research deals with the optimization of the control of chaos by means of evolutionary algorithms. This work is aimed on an explanation of how to use evolutionary algorithms (EAs) and how to properly define the advanced targeting cost function (CF) securing very fast and precise stabilization of desired state for any initial conditions. As a model of deterministic chaotic system, the one dimensional Logistic equation was used. The evolutionary algorithm Self-Organizing Migrating Algorithm (SOMA) was used in four versions. For each version, repeated simulations were conducted to outline the effectiveness and robustness of used method and targeting CF.

An Overview of a Trajectory-Based Solution for En Route and Terminal Area Self-Spacing: Third Revision

NASA Technical Reports Server (NTRS)

Abbott, Terence S.

2012-01-01

This paper presents an overview of the third major revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This algorithm is referred to as the Airborne Spacing for Terminal Arrival Routes version 11 (ASTAR11). This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. Because this algorithm is trajectory-based, it also has the inherent ability to support required time-of-arrival (RTA) operations. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft.

Transform methods for precision continuum and control models of flexible space structures

NASA Technical Reports Server (NTRS)

Lupi, Victor D.; Turner, James D.; Chun, Hon M.

1991-01-01

An open loop optimal control algorithm is developed for general flexible structures, based on Laplace transform methods. A distributed parameter model of the structure is first presented, followed by a derivation of the optimal control algorithm. The control inputs are expressed in terms of their Fourier series expansions, so that a numerical solution can be easily obtained. The algorithm deals directly with the transcendental transfer functions from control inputs to outputs of interest, and structural deformation penalties, as well as penalties on control effort, are included in the formulation. The algorithm is applied to several structures of increasing complexity to show its generality.

Erratum: Erratum: Denoising Phase Unwrapping Algorithm for Precise Phase Shifting Interferometry

NASA Astrophysics Data System (ADS)

Phuc, Phan Huy; Rhee, Hyug-Gyo; Ghim, Young-Sik

2018-06-01

This is a revision of the reference list reported in the original article. In order to clear the contribution of the previous work on the incremental breadth-first search (IBFS) method applied to the PUMA algorithm, we add one more reference to the existing reference list, as in this erratum. Page 83 : In this paper, we propose an algorithm that modifies the Boykov-Kolmogorov (BK) algorithm using the incremental breadth-first search (IBFS) method [27, 28] to find paths from the source to the sink of a graph. [28] S. Ali, H. Khan, I. Shaik and F. Ali, Int. J. Eng. and Technol. 7, 254 (2015).

Experimental Estimation of Entanglement at the Quantum Limit

NASA Astrophysics Data System (ADS)

Brida, Giorgio; Degiovanni, Ivo Pietro; Florio, Angela; Genovese, Marco; Giorda, Paolo; Meda, Alice; Paris, Matteo G. A.; Shurupov, Alexander

2010-03-01

Entanglement is the central resource of quantum information processing and the precise characterization of entangled states is a crucial issue for the development of quantum technologies. This leads to the necessity of a precise, experimental feasible measure of entanglement. Nevertheless, such measurements are limited both from experimental uncertainties and intrinsic quantum bounds. Here we present an experiment where the amount of entanglement of a family of two-qubit mixed photon states is estimated with the ultimate precision allowed by quantum mechanics.

Detection of supercooled liquid water-topped mixed-phase clouds >from shortwave-infrared satellite observations

NASA Astrophysics Data System (ADS)

NOH, Y. J.; Miller, S. D.; Heidinger, A. K.

2015-12-01

Many studies have demonstrated the utility of multispectral information from satellite passive radiometers for detecting and retrieving the properties of cloud globally, which conventionally utilizes shortwave- and thermal-infrared bands. However, the satellite-derived cloud information comes mainly from cloud top or represents a vertically integrated property. This can produce a large bias in determining cloud phase characteristics, in particular for mixed-phase clouds which are often observed to have supercooled liquid water at cloud top but a predominantly ice phase residing below. The current satellite retrieval algorithms may report these clouds simply as supercooled liquid without any further information regarding the presence of a sub-cloud-top ice phase. More accurate characterization of these clouds is very important for climate models and aviation applications. In this study, we present a physical basis and preliminary results for the algorithm development of supercooled liquid-topped mixed-phase cloud detection using satellite radiometer observations. The detection algorithm is based on differential absorption properties between liquid and ice particles in the shortwave-infrared bands. Solar reflectance data in narrow bands at 1.6 μm and 2.25 μm are used to optically probe below clouds for distinction between supercooled liquid-topped clouds with and without an underlying mixed phase component. Varying solar/sensor geometry and cloud optical properties are also considered. The spectral band combination utilized for the algorithm is currently available on Suomi NPP Visible/Infrared Imaging Radiometer Suite (VIIRS), Himawari-8 Advanced Himawari Imager (AHI), and the future GOES-R Advance Baseline Imager (ABI). When tested on simulated cloud fields from WRF model and synthetic ABI data, favorable results were shown with reasonable threat scores (0.6-0.8) and false alarm rates (0.1-0.2). An ARM/NSA case study applied to VIIRS data also indicated promising potential of the algorithm.

Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR).

PubMed

Chen, Baiyu; Barnhart, Huiman; Richard, Samuel; Robins, Marthony; Colsher, James; Samei, Ehsan

2013-11-01

Volume quantifications of lung nodules with multidetector computed tomography (CT) images provide useful information for monitoring nodule developments. The accuracy and precision of the volume quantification, however, can be impacted by imaging and reconstruction parameters. This study aimed to investigate the impact of iterative reconstruction algorithms on the accuracy and precision of volume quantification with dose and slice thickness as additional variables. Repeated CT images were acquired from an anthropomorphic chest phantom with synthetic nodules (9.5 and 4.8 mm) at six dose levels, and reconstructed with three reconstruction algorithms [filtered backprojection (FBP), adaptive statistical iterative reconstruction (ASiR), and model based iterative reconstruction (MBIR)] into three slice thicknesses. The nodule volumes were measured with two clinical software (A: Lung VCAR, B: iNtuition), and analyzed for accuracy and precision. Precision was found to be generally comparable between FBP and iterative reconstruction with no statistically significant difference noted for different dose levels, slice thickness, and segmentation software. Accuracy was found to be more variable. For large nodules, the accuracy was significantly different between ASiR and FBP for all slice thicknesses with both software, and significantly different between MBIR and FBP for 0.625 mm slice thickness with Software A and for all slice thicknesses with Software B. For small nodules, the accuracy was more similar between FBP and iterative reconstruction, with the exception of ASIR vs FBP at 1.25 mm with Software A and MBIR vs FBP at 0.625 mm with Software A. The systematic difference between the accuracy of FBP and iterative reconstructions highlights the importance of extending current segmentation software to accommodate the image characteristics of iterative reconstructions. In addition, a calibration process may help reduce the dependency of accuracy on reconstruction algorithms, such that volumes quantified from scans of different reconstruction algorithms can be compared. The little difference found between the precision of FBP and iterative reconstructions could be a result of both iterative reconstruction's diminished noise reduction at the edge of the nodules as well as the loss of resolution at high noise levels with iterative reconstruction. The findings do not rule out potential advantage of IR that might be evident in a study that uses a larger number of nodules or repeated scans.

Continuous and unattended measurements of the site preference of nitrous oxide emitted from an agricultural soil using quantum cascade laser spectrometry with intercomparison with isotope ratio mass spectrometry.

PubMed

Yamamoto, Akinori; Uchida, Yoshitaka; Akiyama, Hiroko; Nakajima, Yasuhiro

2014-07-15

The difference between the (15)N natural abundance of (14)N-(15)N-O and (15)N-(14)N-O (site preference; SP) is used to understand the mechanisms underlying N2O emissions from soils. We investigated the use of quantum cascade laser (QCL) absorption spectrometry for continuous and precise analysis of the SP of N2O emitted from a field soil at atmospheric mixing ratios. A QCL-based spectrometer was used to determine the SP of soil-emitted N2O accumulated in a closed chamber system without preconcentration. N2O standards (<2500 ppbv) were used to evaluate the precision of the QCL spectrometry (QCLS) system. CO2 and H2O were removed from the gas samples. Intercomparison measurements of QCLS and isotope ratio mass spectrometry (IRMS) were performed on N2O calibration gases at different mixing ratios. The observed dependency of the QCLS result on the N2O mixing ratio was corrected. Measurement of SP of N2O emitted from the field suggested that the SP of N2O varied from 0 to 40‰ over a period of 1 month. The precisions of the SP measurements (300-2500 ppbv) were <1.9‰ for δ(15)N(α) values, <2.6‰ for δ(15)N(β) values, <2.1‰ for δ(15)N(bulk) values, and <2.1‰ for the SP (1 min averaging time) obtained on a once-an-hour calibrated QCLS system, with a cell temperature control precision of ±0.01 K. Continuous and unattended measurements of the SP of N2O emitted from soils were achieved at low N2O mixing ratios. The accuracy of the QCLS measurements for the SP of N2O was significantly improved by precisely controlling the temperature of the system and by correcting for the concentration dependency of the raw data through an intercomparison with IRMS measurements. Copyright © 2014 John Wiley & Sons, Ltd.

Precision investigations of nuclei and nucleons with the (e, e'. gamma. ) reaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Papanicolas, C.N.; Ammons, E.A.; Cardman, L.S.

1988-11-20

Recent theoretical and experimental investigations of the (e, e'..gamma..) reaction show that it provides a probe of unparalleled precision and selectivity. Experiments aimed towards the isolation of multipole form factors in mixed transitions, the study of continuum excitations in nuclei, and the measurement of the response of the proton are underway at several laboratories.

Secondary Agricultural Education Teachers as Agents of Change in Oklahoma and the Adoption of Precision Agriculture

ERIC Educational Resources Information Center

Nickeson, Beth

2013-01-01

Research indicates that precision agricultural education (PAE) in Oklahoma affects environmental quality, water conservation, and crop yields. The purpose of this mixed methods study was to explore the nature and perceived effectiveness of PAE in Oklahoma secondary agricultural education classes. The study was framed by the diffusion of…

Quick mixing of epoxy components

NASA Technical Reports Server (NTRS)

Dunlap, D. E., Jr.

1981-01-01

Two materials are mixed quickly, thoroughly, and in precise proportion by disposable cartridge. Cartridge mixes components of fast-curing epoxy resins, with no mess, just before they are used. It could also be used in industry and home for caulking, sealing, and patching. Materials to be mixed are initially isolated by cylinder wall within cartridge. Cylinder has vanes, with holes in them, at one end and handle at opposite end. When handle is pulled, grooves on shaft rotate cylinder so that vanes rotate to extrude material A uniformly into material B.

The research of adaptive-exposure on spot-detecting camera in ATP system

NASA Astrophysics Data System (ADS)

Qian, Feng; Jia, Jian-jun; Zhang, Liang; Wang, Jian-Yu

2013-08-01

High precision acquisition, tracking, pointing (ATP) system is one of the key techniques of laser communication. The spot-detecting camera is used to detect the direction of beacon in laser communication link, so that it can get the position information of communication terminal for ATP system. The positioning accuracy of camera decides the capability of laser communication system directly. So the spot-detecting camera in satellite-to-earth laser communication ATP systems needs high precision on target detection. The positioning accuracy of cameras should be better than +/-1μ rad . The spot-detecting cameras usually adopt centroid algorithm to get the position information of light spot on detectors. When the intensity of beacon is moderate, calculation results of centroid algorithm will be precise. But the intensity of beacon changes greatly during communication for distance, atmospheric scintillation, weather etc. The output signal of detector will be insufficient when the camera underexposes to beacon because of low light intensity. On the other hand, the output signal of detector will be saturated when the camera overexposes to beacon because of high light intensity. The calculation accuracy of centroid algorithm becomes worse if the spot-detecting camera underexposes or overexposes, and then the positioning accuracy of camera will be reduced obviously. In order to improve the accuracy, space-based cameras should regulate exposure time in real time according to light intensity. The algorithm of adaptive-exposure technique for spot-detecting camera based on metal-oxide-semiconductor (CMOS) detector is analyzed. According to analytic results, a CMOS camera in space-based laser communication system is described, which utilizes the algorithm of adaptive-exposure to adapting exposure time. Test results from imaging experiment system formed verify the design. Experimental results prove that this design can restrain the reduction of positioning accuracy for the change of light intensity. So the camera can keep stable and high positioning accuracy during communication.

A review on the multivariate statistical methods for dimensional reduction studies

NASA Astrophysics Data System (ADS)

Aik, Lim Eng; Kiang, Lam Chee; Mohamed, Zulkifley Bin; Hong, Tan Wei

2017-05-01

In this research study we have discussed multivariate statistical methods for dimensional reduction, which has been done by various researchers. The reduction of dimensionality is valuable to accelerate algorithm progression, as well as really may offer assistance with the last grouping/clustering precision. A lot of boisterous or even flawed info information regularly prompts a not exactly alluring algorithm progression. Expelling un-useful or dis-instructive information segments may for sure help the algorithm discover more broad grouping locales and principles and generally speaking accomplish better exhibitions on new data set.

Fuzzy PID control algorithm based on PSO and application in BLDC motor

NASA Astrophysics Data System (ADS)

Lin, Sen; Wang, Guanglong

2017-06-01

A fuzzy PID control algorithm is studied based on improved particle swarm optimization (PSO) to perform Brushless DC (BLDC) motor control which has high accuracy, good anti-jamming capability and steady state accuracy compared with traditional PID control. The mathematical and simulation model is established for BLDC motor by simulink software, and the speed loop of the fuzzy PID controller is designed. The simulation results show that the fuzzy PID control algorithm based on PSO has higher stability, high control precision and faster dynamic response speed.

Smart sensors II; Proceedings of the Seminar, San Diego, CA, July 31, August 1, 1980

NASA Astrophysics Data System (ADS)

Barbe, D. F.

1980-01-01

Topics discussed include technology for smart sensors, smart sensors for tracking and surveillance, and techniques and algorithms for smart sensors. Papers are presented on the application of very large scale integrated circuits to smart sensors, imaging charge-coupled devices for deep-space surveillance, ultra-precise star tracking using charge coupled devices, and automatic target identification of blurred images with super-resolution features. Attention is also given to smart sensors for terminal homing, algorithms for estimating image position, and the computational efficiency of multiple image registration algorithms.

A High-Level Language for Modeling Algorithms and Their Properties

NASA Astrophysics Data System (ADS)

Akhtar, Sabina; Merz, Stephan; Quinson, Martin

Designers of concurrent and distributed algorithms usually express them using pseudo-code. In contrast, most verification techniques are based on more mathematically-oriented formalisms such as state transition systems. This conceptual gap contributes to hinder the use of formal verification techniques. Leslie Lamport introduced PlusCal, a high-level algorithmic language that has the "look and feel" of pseudo-code, but is equipped with a precise semantics and includes a high-level expression language based on set theory. PlusCal models can be compiled to TLA + and verified using the model checker tlc.

Super-Resolution Algorithm in Cumulative Virtual Blanking

NASA Astrophysics Data System (ADS)

Montillet, J. P.; Meng, X.; Roberts, G. W.; Woolfson, M. S.

2008-11-01

The proliferation of mobile devices and the emergence of wireless location-based services have generated consumer demand for precise location. In this paper, the MUSIC super-resolution algorithm is applied to time delay estimation for positioning purposes in cellular networks. The goal is to position a Mobile Station with UMTS technology. The problem of Base-Stations herability is solved using Cumulative Virtual Blanking. A simple simulator is presented using DS-SS signal. The results show that MUSIC algorithm improves the time delay estimation in both the cases whether or not Cumulative Virtual Blanking was carried out.

[Medical imaging in tumor precision medicine: opportunities and challenges].

PubMed

Xu, Jingjing; Tan, Yanbin; Zhang, Minming

2017-05-25

Tumor precision medicine is an emerging approach for tumor diagnosis, treatment and prevention, which takes account of individual variability of environment, lifestyle and genetic information. Tumor precision medicine is built up on the medical imaging innovations developed during the past decades, including the new hardware, new imaging agents, standardized protocols, image analysis and multimodal imaging fusion technology. Also the development of automated and reproducible analysis algorithm has extracted large amount of information from image-based features. With the continuous development and mining of tumor clinical and imaging databases, the radiogenomics, radiomics and artificial intelligence have been flourishing. Therefore, these new technological advances bring new opportunities and challenges to the application of imaging in tumor precision medicine.

Evaluation of vertical coordinate and vertical mixing algorithms in the HYbrid-Coordinate Ocean Model (HYCOM)

NASA Astrophysics Data System (ADS)

Halliwell, George R.

Vertical coordinate and vertical mixing algorithms included in the HYbrid Coordinate Ocean Model (HYCOM) are evaluated in low-resolution climatological simulations of the Atlantic Ocean. The hybrid vertical coordinates are isopycnic in the deep ocean interior, but smoothly transition to level (pressure) coordinates near the ocean surface, to sigma coordinates in shallow water regions, and back again to level coordinates in very shallow water. By comparing simulations to climatology, the best model performance is realized using hybrid coordinates in conjunction with one of the three available differential vertical mixing models: the nonlocal K-Profile Parameterization, the NASA GISS level 2 turbulence closure, and the Mellor-Yamada level 2.5 turbulence closure. Good performance is also achieved using the quasi-slab Price-Weller-Pinkel dynamical instability model. Differences among these simulations are too small relative to other errors and biases to identify the "best" vertical mixing model for low-resolution climate simulations. Model performance deteriorates slightly when the Kraus-Turner slab mixed layer model is used with hybrid coordinates. This deterioration is smallest when solar radiation penetrates beneath the mixed layer and when shear instability mixing is included. A simulation performed using isopycnic coordinates to emulate the Miami Isopycnic Coordinate Ocean Model (MICOM), which uses Kraus-Turner mixing without penetrating shortwave radiation and shear instability mixing, demonstrates that the advantages of switching from isopycnic to hybrid coordinates and including more sophisticated turbulence closures outweigh the negative numerical effects of maintaining hybrid vertical coordinates.

Mixed time integration methods for transient thermal analysis of structures

NASA Technical Reports Server (NTRS)

Liu, W. K.

1982-01-01

The computational methods used to predict and optimize the thermal structural behavior of aerospace vehicle structures are reviewed. In general, two classes of algorithms, implicit and explicit, are used in transient thermal analysis of structures. Each of these two methods has its own merits. Due to the different time scales of the mechanical and thermal responses, the selection of a time integration method can be a different yet critical factor in the efficient solution of such problems. Therefore mixed time integration methods for transient thermal analysis of structures are being developed. The computer implementation aspects and numerical evaluation of these mixed time implicit-explicit algorithms in thermal analysis of structures are presented. A computationally useful method of estimating the critical time step for linear quadrilateral element is also given. Numerical tests confirm the stability criterion and accuracy characteristics of the methods. The superiority of these mixed time methods to the fully implicit method or the fully explicit method is also demonstrated.

Mixed time integration methods for transient thermal analysis of structures

NASA Technical Reports Server (NTRS)

Liu, W. K.

1983-01-01

The computational methods used to predict and optimize the thermal-structural behavior of aerospace vehicle structures are reviewed. In general, two classes of algorithms, implicit and explicit, are used in transient thermal analysis of structures. Each of these two methods has its own merits. Due to the different time scales of the mechanical and thermal responses, the selection of a time integration method can be a difficult yet critical factor in the efficient solution of such problems. Therefore mixed time integration methods for transient thermal analysis of structures are being developed. The computer implementation aspects and numerical evaluation of these mixed time implicit-explicit algorithms in thermal analysis of structures are presented. A computationally-useful method of estimating the critical time step for linear quadrilateral element is also given. Numerical tests confirm the stability criterion and accuracy characteristics of the methods. The superiority of these mixed time methods to the fully implicit method or the fully explicit method is also demonstrated.

Soft sensor development for Mooney viscosity prediction in rubber mixing process based on GMMDJITGPR algorithm

NASA Astrophysics Data System (ADS)

Yang, Kai; Chen, Xiangguang; Wang, Li; Jin, Huaiping

2017-01-01

In rubber mixing process, the key parameter (Mooney viscosity), which is used to evaluate the property of the product, can only be obtained with 4-6h delay offline. It is quite helpful for the industry, if the parameter can be estimate on line. Various data driven soft sensors have been used to prediction in the rubber mixing. However, it always not functions well due to the phase and nonlinear property in the process. The purpose of this paper is to develop an efficient soft sensing algorithm to solve the problem. Based on the proposed GMMD local sample selecting criterion, the phase information is extracted in the local modeling. Using the Gaussian local modeling method within Just-in-time (JIT) learning framework, nonlinearity of the process is well handled. Efficiency of the new method is verified by comparing the performance with various mainstream soft sensors, using the samples from real industrial rubber mixing process.

Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

NASA Astrophysics Data System (ADS)

Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

2018-04-01

Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

Inferring gene ontologies from pairwise similarity data

PubMed Central

Kramer, Michael; Dutkowski, Janusz; Yu, Michael; Bafna, Vineet; Ideker, Trey

2014-01-01

Motivation: While the manually curated Gene Ontology (GO) is widely used, inferring a GO directly from -omics data is a compelling new problem. Recognizing that ontologies are a directed acyclic graph (DAG) of terms and hierarchical relations, algorithms are needed that: analyze a full matrix of gene–gene pairwise similarities from -omics data;infer true hierarchical structure in these data rather than enforcing hierarchy as a computational artifact; andrespect biological pleiotropy, by which a term in the hierarchy can relate to multiple higher level terms. Methods addressing these requirements are just beginning to emerge—none has been evaluated for GO inference. Methods: We consider two algorithms [Clique Extracted Ontology (CliXO), LocalFitness] that uniquely satisfy these requirements, compared with methods including standard clustering. CliXO is a new approach that finds maximal cliques in a network induced by progressive thresholding of a similarity matrix. We evaluate each method’s ability to reconstruct the GO biological process ontology from a similarity matrix based on (a) semantic similarities for GO itself or (b) three -omics datasets for yeast. Results: For task (a) using semantic similarity, CliXO accurately reconstructs GO (>99% precision, recall) and outperforms other approaches (<20% precision, <20% recall). For task (b) using -omics data, CliXO outperforms other methods using two -omics datasets and achieves ∼30% precision and recall using YeastNet v3, similar to an earlier approach (Network Extracted Ontology) and better than LocalFitness or standard clustering (20–25% precision, recall). Conclusion: This study provides algorithmic foundation for building gene ontologies by capturing hierarchical and pleiotropic structure embedded in biomolecular data. Contact: tideker@ucsd.edu PMID:24932003

A classification model of Hyperion image base on SAM combined decision tree

NASA Astrophysics Data System (ADS)

Wang, Zhenghai; Hu, Guangdao; Zhou, YongZhang; Liu, Xin

2009-10-01

Monitoring the Earth using imaging spectrometers has necessitated more accurate analyses and new applications to remote sensing. A very high dimensional input space requires an exponentially large amount of data to adequately and reliably represent the classes in that space. On the other hand, with increase in the input dimensionality the hypothesis space grows exponentially, which makes the classification performance highly unreliable. Traditional classification algorithms Classification of hyperspectral images is challenging. New algorithms have to be developed for hyperspectral data classification. The Spectral Angle Mapper (SAM) is a physically-based spectral classification that uses an ndimensional angle to match pixels to reference spectra. The algorithm determines the spectral similarity between two spectra by calculating the angle between the spectra, treating them as vectors in a space with dimensionality equal to the number of bands. The key and difficulty is that we should artificial defining the threshold of SAM. The classification precision depends on the rationality of the threshold of SAM. In order to resolve this problem, this paper proposes a new automatic classification model of remote sensing image using SAM combined with decision tree. It can automatic choose the appropriate threshold of SAM and improve the classify precision of SAM base on the analyze of field spectrum. The test area located in Heqing Yunnan was imaged by EO_1 Hyperion imaging spectrometer using 224 bands in visual and near infrared. The area included limestone areas, rock fields, soil and forests. The area was classified into four different vegetation and soil types. The results show that this method choose the appropriate threshold of SAM and eliminates the disturbance and influence of unwanted objects effectively, so as to improve the classification precision. Compared with the likelihood classification by field survey data, the classification precision of this model heightens 9.9%.

Dynamic Distributed Cooperative Control of Multiple Heterogeneous Resources

DTIC Science & Technology

2012-10-01

of the UAVs to maximize the total sensor footprint over the region of interest. The algorithm utilized to solve this problem was based on sampling a...and moving obstacles. Obstacle positions were assumed known a priori. Kingston and Beard [22] presented an algorithm to keep moving UAVs equally spaced...Planning Algorithms , Cambridge University Press, 2006. 11. Ma, C. S. and Miller, R. H., “Mixed integer linear programming trajectory generation for

A Composite Algorithm for Mixed Integer Constrained Nonlinear Optimization.

DTIC Science & Technology

1980-01-01

de Silva [141, and Weisman and Wood [76). A particular direct search algorithm, the simplex method, has been cited for having the potential for...spaced discrete points on a line which makes the direction suitable for an efficient integer search technique based on Fibonacci numbers. Two...defined by a subset of variables. The complex algorithm is particularly well suited for this subspace search for two reasons. First, the complex method

Rigorous high-precision enclosures of fixed points and their invariant manifolds

NASA Astrophysics Data System (ADS)

Wittig, Alexander N.

The well established concept of Taylor Models is introduced, which offer highly accurate C0 enclosures of functional dependencies, combining high-order polynomial approximation of functions and rigorous estimates of the truncation error, performed using verified arithmetic. The focus of this work is on the application of Taylor Models in algorithms for strongly non-linear dynamical systems. A method is proposed to extend the existing implementation of Taylor Models in COSY INFINITY from double precision coefficients to arbitrary precision coefficients. Great care is taken to maintain the highest efficiency possible by adaptively adjusting the precision of higher order coefficients in the polynomial expansion. High precision operations are based on clever combinations of elementary floating point operations yielding exact values for round-off errors. An experimental high precision interval data type is developed and implemented. Algorithms for the verified computation of intrinsic functions based on the High Precision Interval datatype are developed and described in detail. The application of these operations in the implementation of High Precision Taylor Models is discussed. An application of Taylor Model methods to the verification of fixed points is presented by verifying the existence of a period 15 fixed point in a near standard Henon map. Verification is performed using different verified methods such as double precision Taylor Models, High Precision intervals and High Precision Taylor Models. Results and performance of each method are compared. An automated rigorous fixed point finder is implemented, allowing the fully automated search for all fixed points of a function within a given domain. It returns a list of verified enclosures of each fixed point, optionally verifying uniqueness within these enclosures. An application of the fixed point finder to the rigorous analysis of beam transfer maps in accelerator physics is presented. Previous work done by Johannes Grote is extended to compute very accurate polynomial approximations to invariant manifolds of discrete maps of arbitrary dimension around hyperbolic fixed points. The algorithm presented allows for automatic removal of resonances occurring during construction. A method for the rigorous enclosure of invariant manifolds of continuous systems is introduced. Using methods developed for discrete maps, polynomial approximations of invariant manifolds of hyperbolic fixed points of ODEs are obtained. These approximations are outfit with a sharp error bound which is verified to rigorously contain the manifolds. While we focus on the three dimensional case, verification in higher dimensions is possible using similar techniques. Integrating the resulting enclosures using the verified COSY VI integrator, the initial manifold enclosures are expanded to yield sharp enclosures of large parts of the stable and unstable manifolds. To demonstrate the effectiveness of this method, we construct enclosures of the invariant manifolds of the Lorenz system and show pictures of the resulting manifold enclosures. To the best of our knowledge, these enclosures are the largest verified enclosures of manifolds in the Lorenz system in existence.

Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. I - Brightness-temperature properties of a time-dependent cloud-radiation model

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Mugnai, Alberto; Cooper, Harry J.; Tripoli, Gregory J.; Xiang, Xuwu

1992-01-01

The relationship between emerging microwave brightness temperatures (T(B)s) and vertically distributed mixtures of liquid and frozen hydrometeors was investigated, using a cloud-radiation model, in order to establish the framework for a hybrid statistical-physical rainfall retrieval algorithm. Although strong relationships were found between the T(B) values and various rain parameters, these correlations are misleading in that the T(B)s are largely controlled by fluctuations in the ice-particle mixing ratios, which in turn are highly correlated to fluctuations in liquid-particle mixing ratios. However, the empirically based T(B)-rain-rate (T(B)-RR) algorithms can still be used as tools for estimating precipitation if the hydrometeor profiles used for T(B)-RR algorithms are not specified in an ad hoc fashion.

Simulation of Long Lived Tracers Using an Improved Empirically-Based Two-Dimensional Model Transport Algorithm

NASA Technical Reports Server (NTRS)

Fleming, Eric L.; Jackman, Charles H.; Stolarski, Richard S.; Considine, David B.

1998-01-01

We have developed a new empirically-based transport algorithm for use in our GSFC two-dimensional transport and chemistry assessment model. The new algorithm contains planetary wave statistics, and parameterizations to account for the effects due to gravity waves and equatorial Kelvin waves. We will present an overview of the new algorithm, and show various model-data comparisons of long-lived tracers as part of the model validation. We will also show how the new algorithm gives substantially better agreement with observations compared to our previous model transport. The new model captures much of the qualitative structure and seasonal variability observed methane, water vapor, and total ozone. These include: isolation of the tropics and winter polar vortex, the well mixed surf-zone region of the winter sub-tropics and mid-latitudes, and the propagation of seasonal signals in the tropical lower stratosphere. Model simulations of carbon-14 and strontium-90 compare fairly well with observations in reproducing the peak in mixing ratio at 20-25 km, and the decrease with altitude in mixing ratio above 25 km. We also ran time dependent simulations of SF6 from which the model mean age of air values were derived. The oldest air (5.5 to 6 years) occurred in the high latitude upper stratosphere during fall and early winter of both hemispheres, and in the southern hemisphere lower stratosphere during late winter and early spring. The latitudinal gradient of the mean ages also compare well with ER-2 aircraft observations in the lower stratosphere.

Improved artificial bee colony algorithm based gravity matching navigation method.

PubMed

Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

2014-07-18

Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position.

Improved Artificial Bee Colony Algorithm Based Gravity Matching Navigation Method

PubMed Central

Gao, Wei; Zhao, Bo; Zhou, Guang Tao; Wang, Qiu Ying; Yu, Chun Yang

2014-01-01

Gravity matching navigation algorithm is one of the key technologies for gravity aided inertial navigation systems. With the development of intelligent algorithms, the powerful search ability of the Artificial Bee Colony (ABC) algorithm makes it possible to be applied to the gravity matching navigation field. However, existing search mechanisms of basic ABC algorithms cannot meet the need for high accuracy in gravity aided navigation. Firstly, proper modifications are proposed to improve the performance of the basic ABC algorithm. Secondly, a new search mechanism is presented in this paper which is based on an improved ABC algorithm using external speed information. At last, modified Hausdorff distance is introduced to screen the possible matching results. Both simulations and ocean experiments verify the feasibility of the method, and results show that the matching rate of the method is high enough to obtain a precise matching position. PMID:25046019

Optimization and experimental realization of the quantum permutation algorithm

NASA Astrophysics Data System (ADS)

Yalçınkaya, I.; Gedik, Z.

2017-12-01

The quantum permutation algorithm provides computational speed-up over classical algorithms for determining the parity of a given cyclic permutation. For its n -qubit implementations, the number of required quantum gates scales quadratically with n due to the quantum Fourier transforms included. We show here for the n -qubit case that the algorithm can be simplified so that it requires only O (n ) quantum gates, which theoretically reduces the complexity of the implementation. To test our results experimentally, we utilize IBM's 5-qubit quantum processor to realize the algorithm by using the original and simplified recipes for the 2-qubit case. It turns out that the latter results in a significantly higher success probability which allows us to verify the algorithm more precisely than the previous experimental realizations. We also verify the algorithm for the first time for the 3-qubit case with a considerable success probability by taking the advantage of our simplified scheme.

Duality quantum algorithm efficiently simulates open quantum systems

PubMed Central

Wei, Shi-Jie; Ruan, Dong; Long, Gui-Lu

2016-01-01

Because of inevitable coupling with the environment, nearly all practical quantum systems are open system, where the evolution is not necessarily unitary. In this paper, we propose a duality quantum algorithm for simulating Hamiltonian evolution of an open quantum system. In contrast to unitary evolution in a usual quantum computer, the evolution operator in a duality quantum computer is a linear combination of unitary operators. In this duality quantum algorithm, the time evolution of the open quantum system is realized by using Kraus operators which is naturally implemented in duality quantum computer. This duality quantum algorithm has two distinct advantages compared to existing quantum simulation algorithms with unitary evolution operations. Firstly, the query complexity of the algorithm is O(d3) in contrast to O(d4) in existing unitary simulation algorithm, where d is the dimension of the open quantum system. Secondly, By using a truncated Taylor series of the evolution operators, this duality quantum algorithm provides an exponential improvement in precision compared with previous unitary simulation algorithm. PMID:27464855

A novel double fine guide sensor design on space telescope

NASA Astrophysics Data System (ADS)

Zhang, Xu-xu; Yin, Da-yi

2018-02-01

To get high precision attitude for space telescope, a double marginal FOV (field of view) FGS (Fine Guide Sensor) is proposed. It is composed of two large area APS CMOS sensors and both share the same lens in main light of sight. More star vectors can be get by two FGS and be used for high precision attitude determination. To improve star identification speed, the vector cross product in inter-star angles for small marginal FOV different from traditional way is elaborated and parallel processing method is applied to pyramid algorithm. The star vectors from two sensors are then used to attitude fusion with traditional QUEST algorithm. The simulation results show that the system can get high accuracy three axis attitudes and the scheme is feasibility.

Strawberry Maturity Neural Network Detectng System Based on Genetic Algorithm

NASA Astrophysics Data System (ADS)

Xu, Liming

The quick and non-detective detection of agriculture product is one of the measures to increase the precision and productivity of harvesting and grading. Having analyzed H frequency of different maturities in different light intensities, the results show that H frequency for the same maturity has little influence in different light intensities; Under the same light intensity, three strawberry maturities are changing in order. After having confirmed the H frequency section to distinguish the different strawberry maturity, the triplelayer feed-forward neural network system to detect strawberry maturity was designed by using genetic algorithm. The test results show that the detecting precision ratio is 91.7%, it takes 160ms to distinguish one strawberry. Therefore, the online non-detective detecting the strawberry maturity could be realized.

Accommodating Chromosome Inversions in Linkage Analysis

PubMed Central

Chen, Gary K.; Slaten, Erin; Ophoff, Roel A.; Lange, Kenneth

2006-01-01

This work develops a population-genetics model for polymorphic chromosome inversions. The model precisely describes how an inversion changes the nature of and approach to linkage equilibrium. The work also describes algorithms and software for allele-frequency estimation and linkage analysis in the presence of an inversion. The linkage algorithms implemented in the software package Mendel estimate recombination parameters and calculate the posterior probability that each pedigree member carries the inversion. Application of Mendel to eight Centre d'Étude du Polymorphisme Humain pedigrees in a region containing a common inversion on 8p23 illustrates its potential for providing more-precise estimates of the location of an unmapped marker or trait gene. Our expanded cytogenetic analysis of these families further identifies inversion carriers and increases the evidence of linkage. PMID:16826515

A naive Bayes algorithm for tissue origin diagnosis (TOD-Bayes) of synchronous multifocal tumors in the hepatobiliary and pancreatic system.

PubMed

Jiang, Weiqin; Shen, Yifei; Ding, Yongfeng; Ye, Chuyu; Zheng, Yi; Zhao, Peng; Liu, Lulu; Tong, Zhou; Zhou, Linfu; Sun, Shuo; Zhang, Xingchen; Teng, Lisong; Timko, Michael P; Fan, Longjiang; Fang, Weijia

2018-01-15

Synchronous multifocal tumors are common in the hepatobiliary and pancreatic system but because of similarities in their histological features, oncologists have difficulty in identifying their precise tissue clonal origin through routine histopathological methods. To address this problem and assist in more precise diagnosis, we developed a computational approach for tissue origin diagnosis based on naive Bayes algorithm (TOD-Bayes) using ubiquitous RNA-Seq data. Massive tissue-specific RNA-Seq data sets were first obtained from The Cancer Genome Atlas (TCGA) and ∼1,000 feature genes were used to train and validate the TOD-Bayes algorithm. The accuracy of the model was >95% based on tenfold cross validation by the data from TCGA. A total of 18 clinical cancer samples (including six negative controls) with definitive tissue origin were subsequently used for external validation and 17 of the 18 samples were classified correctly in our study (94.4%). Furthermore, we included as cases studies seven tumor samples, taken from two individuals who suffered from synchronous multifocal tumors across tissues, where the efforts to make a definitive primary cancer diagnosis by traditional diagnostic methods had failed. Using our TOD-Bayes analysis, the two clinical test cases were successfully diagnosed as pancreatic cancer (PC) and cholangiocarcinoma (CC), respectively, in agreement with their clinical outcomes. Based on our findings, we believe that the TOD-Bayes algorithm is a powerful novel methodology to accurately identify the tissue origin of synchronous multifocal tumors of unknown primary cancers using RNA-Seq data and an important step toward more precision-based medicine in cancer diagnosis and treatment. © 2017 UICC.

Mixed layer depths via Doppler lidar during low-level jet events

NASA Astrophysics Data System (ADS)

Carroll, Brian; Demoz, Belay; Bonin, Timothy; Delgado, Ruben

2018-04-01

A low-level jet (LLJ) is a prominent wind speed peak in the lower troposphere. Nocturnal LLJs have been shown to transport and mix atmospheric constituents from the residual layer down to the surface, breaching quiescent nocturnal conditions due to high wind shear. A new fuzzy logic algorithm combining turbulence and aerosol information from Doppler lidar scans can resolve the strength and depth of this mixing below the jet. Conclusions will be drawn about LLJ relations to turbulence and mixing.

On the mixing time in the Wang-Landau algorithm

NASA Astrophysics Data System (ADS)

Fadeeva, Marina; Shchur, Lev

2018-01-01

We present preliminary results of the investigation of the properties of the Markov random walk in the energy space generated by the Wang-Landau probability. We build transition matrix in the energy space (TMES) using the exact density of states for one-dimensional and two-dimensional Ising models. The spectral gap of TMES is inversely proportional to the mixing time of the Markov chain. We estimate numerically the dependence of the mixing time on the lattice size, and extract the mixing exponent.

Elastic-plastic mixed-iterative finite element analysis: Implementation and performance assessment

NASA Technical Reports Server (NTRS)

Sutjahjo, Edhi; Chamis, Christos C.

1993-01-01

An elastic-plastic algorithm based on Von Mises and associative flow criteria is implemented in MHOST-a mixed iterative finite element analysis computer program developed by NASA Lewis Research Center. The performance of the resulting elastic-plastic mixed-iterative analysis is examined through a set of convergence studies. Membrane and bending behaviors of 4-node quadrilateral shell finite elements are tested for elastic-plastic performance. Generally, the membrane results are excellent, indicating the implementation of elastic-plastic mixed-iterative analysis is appropriate.

A real-time surface inspection system for precision steel balls based on machine vision

NASA Astrophysics Data System (ADS)

Chen, Yi-Ji; Tsai, Jhy-Cherng; Hsu, Ya-Chen

2016-07-01

Precision steel balls are one of the most fundament components for motion and power transmission parts and they are widely used in industrial machinery and the automotive industry. As precision balls are crucial for the quality of these products, there is an urgent need to develop a fast and robust system for inspecting defects of precision steel balls. In this paper, a real-time system for inspecting surface defects of precision steel balls is developed based on machine vision. The developed system integrates a dual-lighting system, an unfolding mechanism and inspection algorithms for real-time signal processing and defect detection. The developed system is tested under feeding speeds of 4 pcs s-1 with a detection rate of 99.94% and an error rate of 0.10%. The minimum detectable surface flaw area is 0.01 mm2, which meets the requirement for inspecting ISO grade 100 precision steel balls.

Pb and Sr isotope measurements by inductively coupled plasma mass spectrometer: efficient time management for precision improvement

NASA Astrophysics Data System (ADS)

Monna, F.; Loizeau, J.-L.; Thomas, B. A.; Guéguen, C.; Favarger, P.-Y.

1998-08-01

One of the factors limiting the precision of inductively coupled plasma mass spectrometry is the counting statistics, which depend upon acquisition time and ion fluxes. In the present study, the precision of the isotopic measurements of Pb and Sr is examined. The time of measurement is optimally shared for each isotope, using a mathematical simulation, to provide the lowest theoretical analytical error. Different algorithms of mass bias correction are also taken into account and evaluated in term of improvement of overall precision. Several experiments allow a comparison of real conditions with theory. The present method significantly improves the precision, regardless of the instrument used. However, this benefit is more important for equipment which originally yields a precision close to that predicted by counting statistics. Additionally, the procedure is flexible enough to be easily adapted to other problems, such as isotopic dilution.

Hardware-In-The-Loop Testing of Continuous Control Algorithms for a Precision Formation Flying Demonstration Mission

NASA Technical Reports Server (NTRS)

Naasz, Bo J.; Burns, Richard D.; Gaylor, David; Higinbotham, John

2004-01-01

A sample mission sequence is defined for a low earth orbit demonstration of Precision Formation Flying (PFF). Various guidance navigation and control strategies are discussed for use in the PFF experiment phases. A sample PFF experiment is implemented and tested in a realistic Hardware-in-the-Loop (HWIL) simulation using the Formation Flying Test Bed (FFTB) at NASA's Goddard Space Flight Center.

FOCUSR: Feature Oriented Correspondence using Spectral Regularization–A Method for Precise Surface Matching

PubMed Central

Lombaert, Herve; Grady, Leo; Polimeni, Jonathan R.; Cheriet, Farida

2013-01-01

Existing methods for surface matching are limited by the trade-off between precision and computational efficiency. Here we present an improved algorithm for dense vertex-to-vertex correspondence that uses direct matching of features defined on a surface and improves it by using spectral correspondence as a regularization. This algorithm has the speed of both feature matching and spectral matching while exhibiting greatly improved precision (distance errors of 1.4%). The method, FOCUSR, incorporates implicitly such additional features to calculate the correspondence and relies on the smoothness of the lowest-frequency harmonics of a graph Laplacian to spatially regularize the features. In its simplest form, FOCUSR is an improved spectral correspondence method that nonrigidly deforms spectral embeddings. We provide here a full realization of spectral correspondence where virtually any feature can be used as additional information using weights on graph edges, but also on graph nodes and as extra embedded coordinates. As an example, the full power of FOCUSR is demonstrated in a real case scenario with the challenging task of brain surface matching across several individuals. Our results show that combining features and regularizing them in a spectral embedding greatly improves the matching precision (to a sub-millimeter level) while performing at much greater speed than existing methods. PMID:23868776

Precise determination of anthropometric dimensions by means of image processing methods for estimating human body segment parameter values.

PubMed

Baca, A

1996-04-01

A method has been developed for the precise determination of anthropometric dimensions from the video images of four different body configurations. High precision is achieved by incorporating techniques for finding the location of object boundaries with sub-pixel accuracy, the implementation of calibration algorithms, and by taking into account the varying distances of the body segments from the recording camera. The system allows automatic segment boundary identification from the video image, if the boundaries are marked on the subject by black ribbons. In connection with the mathematical finite-mass-element segment model of Hatze, body segment parameters (volumes, masses, the three principal moments of inertia, the three local coordinates of the segmental mass centers etc.) can be computed by using the anthropometric data determined videometrically as input data. Compared to other, recently published video-based systems for the estimation of the inertial properties of body segments, the present algorithms reduce errors originating from optical distortions, inaccurate edge-detection procedures, and user-specified upper and lower segment boundaries or threshold levels for the edge-detection. The video-based estimation of human body segment parameters is especially useful in situations where ease of application and rapid availability of comparatively precise parameter values are of importance.

Computing Generalized Matrix Inverse on Spiking Neural Substrate

PubMed Central

Shukla, Rohit; Khoram, Soroosh; Jorgensen, Erik; Li, Jing; Lipasti, Mikko; Wright, Stephen

2018-01-01

Emerging neural hardware substrates, such as IBM's TrueNorth Neurosynaptic System, can provide an appealing platform for deploying numerical algorithms. For example, a recurrent Hopfield neural network can be used to find the Moore-Penrose generalized inverse of a matrix, thus enabling a broad class of linear optimizations to be solved efficiently, at low energy cost. However, deploying numerical algorithms on hardware platforms that severely limit the range and precision of representation for numeric quantities can be quite challenging. This paper discusses these challenges and proposes a rigorous mathematical framework for reasoning about range and precision on such substrates. The paper derives techniques for normalizing inputs and properly quantizing synaptic weights originating from arbitrary systems of linear equations, so that solvers for those systems can be implemented in a provably correct manner on hardware-constrained neural substrates. The analytical model is empirically validated on the IBM TrueNorth platform, and results show that the guarantees provided by the framework for range and precision hold under experimental conditions. Experiments with optical flow demonstrate the energy benefits of deploying a reduced-precision and energy-efficient generalized matrix inverse engine on the IBM TrueNorth platform, reflecting 10× to 100× improvement over FPGA and ARM core baselines. PMID:29593483

Logit-normal mixed model for Indian monsoon precipitation

NASA Astrophysics Data System (ADS)

Dietz, L. R.; Chatterjee, S.

2014-09-01

Describing the nature and variability of Indian monsoon precipitation is a topic of much debate in the current literature. We suggest the use of a generalized linear mixed model (GLMM), specifically, the logit-normal mixed model, to describe the underlying structure of this complex climatic event. Four GLMM algorithms are described and simulations are performed to vet these algorithms before applying them to the Indian precipitation data. The logit-normal model was applied to light, moderate, and extreme rainfall. Findings indicated that physical constructs were preserved by the models, and random effects were significant in many cases. We also found GLMM estimation methods were sensitive to tuning parameters and assumptions and therefore, recommend use of multiple methods in applications. This work provides a novel use of GLMM and promotes its addition to the gamut of tools for analysis in studying climate phenomena.

Analytical and quasi-Bayesian methods as development of the iterative approach for mixed radiation biodosimetry.

PubMed

Słonecka, Iwona; Łukasik, Krzysztof; Fornalski, Krzysztof W

2018-06-04

The present paper proposes two methods of calculating components of the dose absorbed by the human body after exposure to a mixed neutron and gamma radiation field. The article presents a novel approach to replace the common iterative method in its analytical form, thus reducing the calculation time. It also shows a possibility of estimating the neutron and gamma doses when their ratio in a mixed beam is not precisely known.

Transactional Algorithm for Subtracting Fractions: Go Shopping

ERIC Educational Resources Information Center

Pinckard, James Seishin

2009-01-01

The purpose of this quasi-experimental research study was to examine the effects of an alternative or transactional algorithm for subtracting mixed numbers within the middle school setting. Initial data were gathered from the student achievement of four mathematics teachers at three different school sites. The results indicated students who…

Over 20 years of reaction access systems from MDL: a novel reaction substructure search algorithm.

PubMed

Chen, Lingran; Nourse, James G; Christie, Bradley D; Leland, Burton A; Grier, David L

2002-01-01

From REACCS, to MDL ISIS/Host Reaction Gateway, and most recently to MDL Relational Chemistry Server, a new product based on Oracle data cartridge technology, MDL's reaction database management and retrieval systems have undergone great changes. The evolution of the system architecture is briefly discussed. The evolution of MDL reaction substructure search (RSS) algorithms is detailed. This article mainly describes a novel RSS algorithm. This algorithm is based on a depth-first search approach and is able to fully and prospectively use reaction specific information, such as reacting center and atom-atom mapping (AAM) information. The new algorithm has been used in the recently released MDL Relational Chemistry Server and allows the user to precisely find reaction instances in databases while minimizing unrelated hits. Finally, the existing and new RSS algorithms are compared with several examples.

Neutrino oscillations: The rise of the PMNS paradigm

NASA Astrophysics Data System (ADS)

Giganti, C.; Lavignac, S.; Zito, M.

2018-01-01

Since the discovery of neutrino oscillations, the experimental progress in the last two decades has been very fast, with the precision measurements of the neutrino squared-mass differences and of the mixing angles, including the last unknown mixing angle θ13. Today a very large set of oscillation results obtained with a variety of experimental configurations and techniques can be interpreted in the framework of three active massive neutrinos, whose mass and flavour eigenstates are related by a 3 × 3 unitary mixing matrix, the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) matrix, parametrized by three mixing angles θ12, θ23, θ13 and a CP-violating phase δCP. The additional parameters governing neutrino oscillations are the squared-mass differences Δ mji2 = mj2 - mi2, where mi is the mass of the ith neutrino mass eigenstate. This review covers the rise of the PMNS three-neutrino mixing paradigm and the current status of the experimental determination of its parameters. The next years will continue to see a rich program of experimental endeavour coming to fruition and addressing the three missing pieces of the puzzle, namely the determination of the octant and precise value of the mixing angle θ23, the unveiling of the neutrino mass ordering (whether m1

The Value of Developing a Mixed-Methods Program of Research.

PubMed

Simonovich, Shannon

2017-07-01

This article contributes to the discussion of the value of utilizing mixed methodological approaches to conduct nursing research. To this end, the author of this article proposes creating a mixed-methods program of research over time, where both quantitative and qualitative data are collected and analyzed simultaneously, rather than focusing efforts on designing singular mixed-methods studies. A mixed-methods program of research would allow for the best of both worlds: precision through focus on one method at a time, and the benefits of creating a robust understanding of a phenomenon over the trajectory of one's career through examination from various methodological approaches.

Carrier-separating demodulation of phase shifting self-mixing interferometry

NASA Astrophysics Data System (ADS)

Tao, Yufeng; Wang, Ming; Xia, Wei

2017-03-01

A carrier separating method associated with noise-elimination had been introduced into a sinusoidal phase-shifting self-mixing interferometer. The conventional sinusoidal phase shifting self-mixing interferometry was developed into a more competitive instrument with high computing efficiency and nanometer accuracy of λ / 100 in dynamical vibration measurement. The high slew rate electro-optic modulator induced a sinusoidal phase carrier with ultralow insertion loss in this paper. In order to extract phase-shift quickly and precisely, this paper employed the carrier-separating to directly generate quadrature signals without complicated frequency domain transforms. Moreover, most noises were evaluated and suppressed by a noise-elimination technology synthesizing empirical mode decomposition with wavelet transform. The overall laser system was described and inherent advantages such as high computational efficiency and decreased nonlinear errors of the established system were demonstrated. The experiment implemented on a high precision PZT (positioning accuracy was better than 1 nm) and compared with laser Doppler velocity meter. The good agreement of two instruments shown that the short-term resolution had improved from 10 nm to 1.5 nm in dynamic vibration measurement with reduced time expense. This was useful in precision measurement to improve the SMI with same sampling rate. The proposed signal processing was performed in pure time-domain requiring no preprocessing electronic circuits.

Centroiding Experiment for Determining the Positions of Stars with High Precision

NASA Astrophysics Data System (ADS)

Yano, T.; Araki, H.; Hanada, H.; Tazawa, S.; Gouda, N.; Kobayashi, Y.; Yamada, Y.; Niwa, Y.

2010-12-01

We have experimented with the determination of the positions of star images on a detector with high precision such as 10 microarcseconds, required by a space astrometry satellite, JASMINE. In order to accomplish such a precision, we take the following two procedures. (1) We determine the positions of star images on the detector with the precision of about 0.01 pixel for one measurement, using an algorithm for estimating them from photon weighted means of the star images. (2) We determine the positions of star images with the precision of about 0.0001-0.00001 pixel, which corresponds to that of 10 microarcseconds, using a large amount of data over 10000 measurements, that is, the error of the positions decreases according to the amount of data. Here, we note that the procedure 2 is not accomplished when the systematic error in our data is not excluded adequately even if we use a large amount of data. We first show the method to determine the positions of star images on the detector using photon weighted means of star images. This algorithm, used in this experiment, is very useful because it is easy to calculate the photon weighted mean from the data. This is very important in treating a large amount of data. Furthermore, we need not assume the shape of the point spread function in deriving the centroid of star images. Second, we show the results in the laboratory experiment for precision of determining the positions of star images. We obtain that the precision of estimation of positions of star images on the detector is under a variance of 0.01 pixel for one measurement (procedure 1). We also obtain that the precision of the positions of star images becomes a variance of about 0.0001 pixel using about 10000 measurements (procedure 2).

Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

NASA Astrophysics Data System (ADS)

Ahmad, Siti Rohaidah; Yusop, Nurhafizah Moziyana Mohd; Bakar, Azuraliza Abu; Yaakub, Mohd Ridzwan

2017-10-01

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

Monte Carlo algorithms for Brownian phylogenetic models.

PubMed

Horvilleur, Benjamin; Lartillot, Nicolas

2014-11-01

Brownian models have been introduced in phylogenetics for describing variation in substitution rates through time, with applications to molecular dating or to the comparative analysis of variation in substitution patterns among lineages. Thus far, however, the Monte Carlo implementations of these models have relied on crude approximations, in which the Brownian process is sampled only at the internal nodes of the phylogeny or at the midpoints along each branch, and the unknown trajectory between these sampled points is summarized by simple branchwise average substitution rates. A more accurate Monte Carlo approach is introduced, explicitly sampling a fine-grained discretization of the trajectory of the (potentially multivariate) Brownian process along the phylogeny. Generic Monte Carlo resampling algorithms are proposed for updating the Brownian paths along and across branches. Specific computational strategies are developed for efficient integration of the finite-time substitution probabilities across branches induced by the Brownian trajectory. The mixing properties and the computational complexity of the resulting Markov chain Monte Carlo sampler scale reasonably with the discretization level, allowing practical applications with up to a few hundred discretization points along the entire depth of the tree. The method can be generalized to other Markovian stochastic processes, making it possible to implement a wide range of time-dependent substitution models with well-controlled computational precision. The program is freely available at www.phylobayes.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Parameterization-based tracking for the P2 experiment

NASA Astrophysics Data System (ADS)

Sorokin, Iurii

2017-08-01

The P2 experiment in Mainz aims to determine the weak mixing angle θW at low momentum transfer by measuring the parity-violating asymmetry of elastic electronproton scattering. In order to achieve the intended precision of Δ(sin2 θW)/sin2θW = 0:13% within the planned 10 000 hours of running the experiment has to operate at the rate of 1011 detected electrons per second. Although it is not required to measure the kinematic parameters of each individual electron, every attempt is made to achieve the highest possible throughput in the track reconstruction chain. In the present work a parameterization-based track reconstruction method is described. It is a variation of track following, where the results of the computation-heavy steps, namely the propagation of a track to the further detector plane, and the fitting, are pre-calculated, and expressed in terms of parametric analytic functions. This makes the algorithm extremely fast, and well-suited for an implementation on an FPGA. The method also takes implicitly into account the actual phase space distribution of the tracks already at the stage of candidate construction. Compared to a simple algorithm, that does not use such information, this allows reducing the combinatorial background by many orders of magnitude, down to O(1) background candidate per one signal track. The method is developed specifically for the P2 experiment in Mainz, and the presented implementation is tightly coupled to the experimental conditions.

NIMROD: a program for inference via a normal approximation of the posterior in models with random effects based on ordinary differential equations.

PubMed

Prague, Mélanie; Commenges, Daniel; Guedj, Jérémie; Drylewicz, Julia; Thiébaut, Rodolphe

2013-08-01

Models based on ordinary differential equations (ODE) are widespread tools for describing dynamical systems. In biomedical sciences, data from each subject can be sparse making difficult to precisely estimate individual parameters by standard non-linear regression but information can often be gained from between-subjects variability. This makes natural the use of mixed-effects models to estimate population parameters. Although the maximum likelihood approach is a valuable option, identifiability issues favour Bayesian approaches which can incorporate prior knowledge in a flexible way. However, the combination of difficulties coming from the ODE system and from the presence of random effects raises a major numerical challenge. Computations can be simplified by making a normal approximation of the posterior to find the maximum of the posterior distribution (MAP). Here we present the NIMROD program (normal approximation inference in models with random effects based on ordinary differential equations) devoted to the MAP estimation in ODE models. We describe the specific implemented features such as convergence criteria and an approximation of the leave-one-out cross-validation to assess the model quality of fit. In pharmacokinetics models, first, we evaluate the properties of this algorithm and compare it with FOCE and MCMC algorithms in simulations. Then, we illustrate NIMROD use on Amprenavir pharmacokinetics data from the PUZZLE clinical trial in HIV infected patients. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

NASA Technical Reports Server (NTRS)

Lo, Ching F.

1999-01-01

The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.

How to Compute a Slot Marker - Calculation of Controller Managed Spacing Tools for Efficient Descents with Precision Scheduling

NASA Technical Reports Server (NTRS)

Prevot, Thomas

2012-01-01

This paper describes the underlying principles and algorithms for computing the primary controller managed spacing (CMS) tools developed at NASA for precisely spacing aircraft along efficient descent paths. The trajectory-based CMS tools include slot markers, delay indications and speed advisories. These tools are one of three core NASA technologies integrated in NASAs ATM technology demonstration-1 (ATD-1) that will operationally demonstrate the feasibility of fuel-efficient, high throughput arrival operations using Automatic Dependent Surveillance Broadcast (ADS-B) and ground-based and airborne NASA technologies for precision scheduling and spacing.

Automatic motor task selection via a bandit algorithm for a brain-controlled button

NASA Astrophysics Data System (ADS)

Fruitet, Joan; Carpentier, Alexandra; Munos, Rémi; Clerc, Maureen

2013-02-01

Objective. Brain-computer interfaces (BCIs) based on sensorimotor rhythms use a variety of motor tasks, such as imagining moving the right or left hand, the feet or the tongue. Finding the tasks that yield best performance, specifically to each user, is a time-consuming preliminary phase to a BCI experiment. This study presents a new adaptive procedure to automatically select (online) the most promising motor task for an asynchronous brain-controlled button. Approach. We develop for this purpose an adaptive algorithm UCB-classif based on the stochastic bandit theory and design an EEG experiment to test our method. We compare (offline) the adaptive algorithm to a naïve selection strategy which uses uniformly distributed samples from each task. We also run the adaptive algorithm online to fully validate the approach. Main results. By not wasting time on inefficient tasks, and focusing on the most promising ones, this algorithm results in a faster task selection and a more efficient use of the BCI training session. More precisely, the offline analysis reveals that the use of this algorithm can reduce the time needed to select the most appropriate task by almost half without loss in precision, or alternatively, allow us to investigate twice the number of tasks within a similar time span. Online tests confirm that the method leads to an optimal task selection. Significance. This study is the first one to optimize the task selection phase by an adaptive procedure. By increasing the number of tasks that can be tested in a given time span, the proposed method could contribute to reducing ‘BCI illiteracy’.

Direct and precise measurement of displacement and velocity of flexible web in roll-to-roll manufacturing systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Dongwoo; Lee, Eonseok; Choi, Young-Man

Interest in the production of printed electronics using a roll-to-roll system has gradually increased due to its low mass-production costs and compatibility with flexible substrate. To improve the accuracy of roll-to-roll manufacturing systems, the movement of the web needs to be measured precisely in advance. In this paper, a novel measurement method is developed to measure the displacement and velocity of the web precisely and directly. The proposed algorithm is based on the traditional single field encoder principle, and the scale grating has been replaced with a printed grating on the web. Because a printed grating cannot be as accuratemore » as a scale grating in a traditional encoder, there will inevitably be variations in pitch and line-width, and the motion of the web should be measured even though there are variations in pitch and line-width in the printed grating patterns. For this reason, the developed algorithm includes a precise method of estimating the variations in pitch. In addtion, a method of correcting the Lissajous curve is presented for precision phase interpolation to improve measurement accuracy by correcting Lissajous circle to unit circle. The performance of the developed method is evaluated by simulation and experiment. In the experiment, the displacement error was less than 2.5 μm and the velocity error of 1σ was about 0.25%, while the grating scale moved 30 mm.« less

Direct and precise measurement of displacement and velocity of flexible web in roll-to-roll manufacturing systems

NASA Astrophysics Data System (ADS)

Kang, Dongwoo; duk Kim, Young; Lee, Eonseok; Choi, Young-Man; Lee, Taik-Min; Kim, Dongmin

2013-12-01

Interest in the production of printed electronics using a roll-to-roll system has gradually increased due to its low mass-production costs and compatibility with flexible substrate. To improve the accuracy of roll-to-roll manufacturing systems, the movement of the web needs to be measured precisely in advance. In this paper, a novel measurement method is developed to measure the displacement and velocity of the web precisely and directly. The proposed algorithm is based on the traditional single field encoder principle, and the scale grating has been replaced with a printed grating on the web. Because a printed grating cannot be as accurate as a scale grating in a traditional encoder, there will inevitably be variations in pitch and line-width, and the motion of the web should be measured even though there are variations in pitch and line-width in the printed grating patterns. For this reason, the developed algorithm includes a precise method of estimating the variations in pitch. In addtion, a method of correcting the Lissajous curve is presented for precision phase interpolation to improve measurement accuracy by correcting Lissajous circle to unit circle. The performance of the developed method is evaluated by simulation and experiment. In the experiment, the displacement error was less than 2.5 μm and the velocity error of 1σ was about 0.25%, while the grating scale moved 30 mm.

Solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators.

PubMed

Zhao, Jing; Zong, Haili

2018-01-01

In this paper, we propose parallel and cyclic iterative algorithms for solving the multiple-set split equality common fixed-point problem of firmly quasi-nonexpansive operators. We also combine the process of cyclic and parallel iterative methods and propose two mixed iterative algorithms. Our several algorithms do not need any prior information about the operator norms. Under mild assumptions, we prove weak convergence of the proposed iterative sequences in Hilbert spaces. As applications, we obtain several iterative algorithms to solve the multiple-set split equality problem.

High-precision two-dimensional atom localization from four-wave mixing in a double-Λ four-level atomic system

NASA Astrophysics Data System (ADS)

Shui, Tao; Yang, Wen-Xing; Chen, Ai-Xi; Liu, Shaopeng; Li, Ling; Zhu, Zhonghu

2018-03-01

We propose a scheme for high-precision two-dimensional (2D) atom localization via the four-wave mixing (FWM) in a four-level double-Λ atomic system. Due to the position-dependent atom-field interaction, the 2D position information of the atoms can be directly determined by the measurement of the normalized light intensity of output FWM-generated field. We further show that, when the position-dependent generated FWM field has become sufficiently intense, efficient back-coupling to the FWM generating state becomes important. This back-coupling pathway leads to competitive multiphoton destructive interference of the FWM generating state by three supplied and one internally generated fields. We find that the precision of 2D atom localization can be improved significantly by the multiphoton destructive interference and depends sensitively on the frequency detunings and the pump field intensity. Interestingly enough, we show that adjusting the frequency detunings and the pump field intensity can modify significantly the FWM efficiency, and consequently lead to a redistribution of the atoms. As a result, the atom can be localized in one of four quadrants with holding the precision of atom localization.

Design and control of a macro-micro robot for precise force applications

NASA Technical Reports Server (NTRS)

Wang, Yulun; Mangaser, Amante; Laby, Keith; Jordan, Steve; Wilson, Jeff

1993-01-01

Creating a robot which can delicately interact with its environment has been the goal of much research. Primarily two difficulties have made this goal hard to attain. The execution of control strategies which enable precise force manipulations are difficult to implement in real time because such algorithms have been too computationally complex for available controllers. Also, a robot mechanism which can quickly and precisely execute a force command is difficult to design. Actuation joints must be sufficiently stiff, frictionless, and lightweight so that desired torques can be accurately applied. This paper describes a robotic system which is capable of delicate manipulations. A modular high-performance multiprocessor control system was designed to provide sufficient compute power for executing advanced control methods. An 8 degree of freedom macro-micro mechanism was constructed to enable accurate tip forces. Control algorithms based on the impedance control method were derived, coded, and load balanced for maximum execution speed on the multiprocessor system. Delicate force tasks such as polishing, finishing, cleaning, and deburring, are the target applications of the robot.

Islander: A database of precisely mapped genomic islands in tRNA and tmRNA genes

DOE PAGES

Hudson, Corey M.; Lau, Britney Y.; Williams, Kelly P.

2014-11-05

Genomic islands are mobile DNAs that are major agents of bacterial and archaeal evolution. Integration into prokaryotic chromosomes usually occurs site-specifically at tRNA or tmRNA gene (together, tDNA) targets, catalyzed by tyrosine integrases. This splits the target gene, yet sequences within the island restore the disrupted gene; the regenerated target and its displaced fragment precisely mark the endpoints of the island. We applied this principle to search for islands in genomic DNA sequences. Our algorithm identifies tDNAs, finds fragments of those tDNAs in the same replicon and removes unlikely candidate islands through a series of filters. A search for islandsmore » in 2168 whole prokaryotic genomes produced 3919 candidates. The website Islander (recently moved to http://bioinformatics.sandia.gov/islander/) presents these precisely mapped candidate islands, the gene content and the island sequence. The algorithm further insists that each island encode an integrase, and attachment site sequence identity is carefully noted; therefore, the database also serves in the study of integrase site-specificity and its evolution.« less

High precision innovative micropump for artificial pancreas

NASA Astrophysics Data System (ADS)

Chappel, E.; Mefti, S.; Lettieri, G.-L.; Proennecke, S.; Conan, C.

2014-03-01

The concept of artificial pancreas, which comprises an insulin pump, a continuous glucose meter and a control algorithm, is a major step forward in managing patient with type 1 diabetes mellitus. The stability of the control algorithm is based on short-term precision micropump to deliver rapid-acting insulin and to specific integrated sensors able to monitor any failure leading to a loss of accuracy. Debiotech's MEMS micropump, based on the membrane pump principle, is made of a stack of 3 silicon wafers. The pumping chamber comprises a pillar check-valve at the inlet, a pumping membrane which is actuated against stop limiters by a piezo cantilever, an anti-free-flow outlet valve and a pressure sensor. The micropump inlet is tightly connected to the insulin reservoir while the outlet is in direct communication with the patient skin via a cannula. To meet the requirement of a pump dedicated to closed-loop application for diabetes care, in addition to the well-controlled displacement of the pumping membrane, the high precision of the micropump is based on specific actuation profiles that balance effect of pump elasticity in low-consumption push-pull mode.

Entity recognition in the biomedical domain using a hybrid approach.

PubMed

Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

2017-11-09

This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

Validation of a Natural Language Processing Algorithm for Detecting Infectious Disease Symptoms in Primary Care Electronic Medical Records in Singapore.

PubMed

Hardjojo, Antony; Gunachandran, Arunan; Pang, Long; Abdullah, Mohammed Ridzwan Bin; Wah, Win; Chong, Joash Wen Chen; Goh, Ee Hui; Teo, Sok Huang; Lim, Gilbert; Lee, Mong Li; Hsu, Wynne; Lee, Vernon; Chen, Mark I-Cheng; Wong, Franco; Phang, Jonathan Siung King

2018-06-11

Free-text clinical records provide a source of information that complements traditional disease surveillance. To electronically harness these records, they need to be transformed into codified fields by natural language processing algorithms. The aim of this study was to develop, train, and validate Clinical History Extractor for Syndromic Surveillance (CHESS), an natural language processing algorithm to extract clinical information from free-text primary care records. CHESS is a keyword-based natural language processing algorithm to extract 48 signs and symptoms suggesting respiratory infections, gastrointestinal infections, constitutional, as well as other signs and symptoms potentially associated with infectious diseases. The algorithm also captured the assertion status (affirmed, negated, or suspected) and symptom duration. Electronic medical records from the National Healthcare Group Polyclinics, a major public sector primary care provider in Singapore, were randomly extracted and manually reviewed by 2 human reviewers, with a third reviewer as the adjudicator. The algorithm was evaluated based on 1680 notes against the human-coded result as the reference standard, with half of the data used for training and the other half for validation. The symptoms most commonly present within the 1680 clinical records at the episode level were those typically present in respiratory infections such as cough (744/7703, 9.66%), sore throat (591/7703, 7.67%), rhinorrhea (552/7703, 7.17%), and fever (928/7703, 12.04%). At the episode level, CHESS had an overall performance of 96.7% precision and 97.6% recall on the training dataset and 96.0% precision and 93.1% recall on the validation dataset. Symptoms suggesting respiratory and gastrointestinal infections were all detected with more than 90% precision and recall. CHESS correctly assigned the assertion status in 97.3%, 97.9%, and 89.8% of affirmed, negated, and suspected signs and symptoms, respectively (97.6% overall accuracy). Symptom episode duration was correctly identified in 81.2% of records with known duration status. We have developed an natural language processing algorithm dubbed CHESS that achieves good performance in extracting signs and symptoms from primary care free-text clinical records. In addition to the presence of symptoms, our algorithm can also accurately distinguish affirmed, negated, and suspected assertion statuses and extract symptom durations. ©Antony Hardjojo, Arunan Gunachandran, Long Pang, Mohammed Ridzwan Bin Abdullah, Win Wah, Joash Wen Chen Chong, Ee Hui Goh, Sok Huang Teo, Gilbert Lim, Mong Li Lee, Wynne Hsu, Vernon Lee, Mark I-Cheng Chen, Franco Wong, Jonathan Siung King Phang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 11.06.2018.

Operational Planning for Multiple Heterogeneous Unmanned Aerial Vehicles in Three Dimensions

DTIC Science & Technology

2009-06-01

human input in the planning process. Two solution methods are presented: (1) a mixed-integer program, and (2) an algorithm that utilizes a metaheuristic ...and (2) an algorithm that utilizes a metaheuristic to generate composite variables for a linear program, called the Composite Operations Planning...that represent a path and an associated type of UAV. The reformulation is incorporated into an algorithm that uses a metaheuristic to generate the

A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.

PubMed

Hajri, S; Liouane, N; Hammadi, S; Borne, P

2000-01-01

Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.

Electro-Optic Identification (EOID) Research Program

DTIC Science & Technology

2002-09-30

The goal of this research is to provide computer-assisted identification of underwater mines in electro - optic imagery. Identification algorithms will...greatly reduce the time and risk to reacquire mine-like-objects for positive classification and identification. The objectives are to collect electro ... optic data under a wide range of operating and environmental conditions and develop precise algorithms that can provide accurate target recognition on this data for all possible conditions.

An Online Tilt Estimation and Compensation Algorithm for a Small Satellite Camera

NASA Astrophysics Data System (ADS)

Lee, Da-Hyun; Hwang, Jai-hyuk

2018-04-01

In the case of a satellite camera designed to execute an Earth observation mission, even after a pre-launch precision alignment process has been carried out, misalignment will occur due to external factors during the launch and in the operating environment. In particular, for high-resolution satellite cameras, which require submicron accuracy for alignment between optical components, misalignment is a major cause of image quality degradation. To compensate for this, most high-resolution satellite cameras undergo a precise realignment process called refocusing before and during the operation process. However, conventional Earth observation satellites only execute refocusing upon de-space. Thus, in this paper, an online tilt estimation and compensation algorithm that can be utilized after de-space correction is executed. Although the sensitivity of the optical performance degradation due to the misalignment is highest in de-space, the MTF can be additionally increased by correcting tilt after refocusing. The algorithm proposed in this research can be used to estimate the amount of tilt that occurs by taking star images, and it can also be used to carry out automatic tilt corrections by employing a compensation mechanism that gives angular motion to the secondary mirror. Crucially, this algorithm is developed using an online processing system so that it can operate without communication with the ground.

A Long-Term Performance Enhancement Method for FOG-Based Measurement While Drilling

PubMed Central

Zhang, Chunxi; Lin, Tie

2016-01-01

In the oil industry, the measurement-while-drilling (MWD) systems are usually used to provide the real-time position and orientation of the bottom hole assembly (BHA) during drilling. However, the present MWD systems based on magnetic surveying technology can barely ensure good performance because of magnetic interference phenomena. In this paper, a MWD surveying system based on a fiber optic gyroscope (FOG) was developed to replace the magnetic surveying system. To accommodate the size of the downhole drilling conditions, a new design method is adopted. In order to realize long-term and high position precision and orientation surveying, an integrated surveying algorithm is proposed based on inertial navigation system (INS) and drilling features. In addition, the FOG-based MWD error model is built and the drilling features are analyzed. The state-space system model and the observation updates model of the Kalman filter are built. To validate the availability and utility of the algorithm, the semi-physical simulation is conducted under laboratory conditions. The results comparison with the traditional algorithms show that the errors were suppressed and the measurement precision of the proposed algorithm is better than the traditional ones. In addition, the proposed method uses a lot less time than the zero velocity update (ZUPT) method. PMID:27483270

A Long-Term Performance Enhancement Method for FOG-Based Measurement While Drilling.

PubMed

Zhang, Chunxi; Lin, Tie

2016-07-28

In the oil industry, the measurement-while-drilling (MWD) systems are usually used to provide the real-time position and orientation of the bottom hole assembly (BHA) during drilling. However, the present MWD systems based on magnetic surveying technology can barely ensure good performance because of magnetic interference phenomena. In this paper, a MWD surveying system based on a fiber optic gyroscope (FOG) was developed to replace the magnetic surveying system. To accommodate the size of the downhole drilling conditions, a new design method is adopted. In order to realize long-term and high position precision and orientation surveying, an integrated surveying algorithm is proposed based on inertial navigation system (INS) and drilling features. In addition, the FOG-based MWD error model is built and the drilling features are analyzed. The state-space system model and the observation updates model of the Kalman filter are built. To validate the availability and utility of the algorithm, the semi-physical simulation is conducted under laboratory conditions. The results comparison with the traditional algorithms show that the errors were suppressed and the measurement precision of the proposed algorithm is better than the traditional ones. In addition, the proposed method uses a lot less time than the zero velocity update (ZUPT) method.

A diabetic retinopathy detection method using an improved pillar K-means algorithm.

PubMed

Gogula, Susmitha Valli; Divakar, Ch; Satyanarayana, Ch; Rao, Allam Appa

2014-01-01

The paper presents a new approach for medical image segmentation. Exudates are a visible sign of diabetic retinopathy that is the major reason of vision loss in patients with diabetes. If the exudates extend into the macular area, blindness may occur. Automated detection of exudates will assist ophthalmologists in early diagnosis. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after getting optimized by Pillar algorithm; pillars are constructed in such a way that they can withstand the pressure. Improved pillar algorithm can optimize the K-means clustering for image segmentation in aspects of precision and computation time. This evaluates the proposed approach for image segmentation by comparing with Kmeans and Fuzzy C-means in a medical image. Using this method, identification of dark spot in the retina becomes easier and the proposed algorithm is applied on diabetic retinal images of all stages to identify hard and soft exudates, where the existing pillar K-means is more appropriate for brain MRI images. This proposed system help the doctors to identify the problem in the early stage and can suggest a better drug for preventing further retinal damage.

A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM

PubMed Central

Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei

2018-01-01

Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model’s performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM’s parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models’ performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors. PMID:29342942

A simplified Integer Cosine Transform and its application in image compression

NASA Technical Reports Server (NTRS)

Costa, M.; Tong, K.

1994-01-01

A simplified version of the integer cosine transform (ICT) is described. For practical reasons, the transform is considered jointly with the quantization of its coefficients. It differs from conventional ICT algorithms in that the combined factors for normalization and quantization are approximated by powers of two. In conventional algorithms, the normalization/quantization stage typically requires as many integer divisions as the number of transform coefficients. By restricting the factors to powers of two, these divisions can be performed by variable shifts in the binary representation of the coefficients, with speed and cost advantages to the hardware implementation of the algorithm. The error introduced by the factor approximations is compensated for in the inverse ICT operation, executed with floating point precision. The simplified ICT algorithm has potential applications in image-compression systems with disparate cost and speed requirements in the encoder and decoder ends. For example, in deep space image telemetry, the image processors on board the spacecraft could take advantage of the simplified, faster encoding operation, which would be adjusted on the ground, with high-precision arithmetic. A dual application is found in compressed video broadcasting. Here, a fast, high-performance processor at the transmitter would precompensate for the factor approximations in the inverse ICT operation, to be performed in real time, at a large number of low-cost receivers.

A Fast Approximate Algorithm for Mapping Long Reads to Large Reference Databases.

PubMed

Jain, Chirag; Dilthey, Alexander; Koren, Sergey; Aluru, Srinivas; Phillippy, Adam M

2018-04-30

Emerging single-molecule sequencing technologies from Pacific Biosciences and Oxford Nanopore have revived interest in long-read mapping algorithms. Alignment-based seed-and-extend methods demonstrate good accuracy, but face limited scalability, while faster alignment-free methods typically trade decreased precision for efficiency. In this article, we combine a fast approximate read mapping algorithm based on minimizers with a novel MinHash identity estimation technique to achieve both scalability and precision. In contrast to prior methods, we develop a mathematical framework that defines the types of mapping targets we uncover, establish probabilistic estimates of p-value and sensitivity, and demonstrate tolerance for alignment error rates up to 20%. With this framework, our algorithm automatically adapts to different minimum length and identity requirements and provides both positional and identity estimates for each mapping reported. For mapping human PacBio reads to the hg38 reference, our method is 290 × faster than Burrows-Wheeler Aligner-MEM with a lower memory footprint and recall rate of 96%. We further demonstrate the scalability of our method by mapping noisy PacBio reads (each ≥5 kbp in length) to the complete NCBI RefSeq database containing 838 Gbp of sequence and >60,000 genomes.

Sonic Estimation of Elasticity via Resonance: A New Method of Assessing Hemostasis

PubMed Central

Corey, F. Scott; Walker, William F.

2015-01-01

Uncontrolled bleeding threatens patients undergoing major surgery and in care for traumatic injury. This paper describes a novel method of diagnosing coagulation dysfunction by repeatedly measuring the shear modulus of a blood sample as it clots in vitro. Each measurement applies a high-energy ultrasound pulse to induce a shear wave within a rigid walled chamber, and then uses low energy ultrasound pulses to measure displacements associated with the resonance of that shear wave. Measured displacements are correlated with predictions from Finite Difference Time Domain (FDTD) models, with the best fit corresponding to the modulus estimate. In our current implementation each measurement requires 62.4 ms. Experimental data was analyzed using a fixed-viscosity algorithm and a free-viscosity algorithm. In experiments utilizing human blood induced to clot by exposure to kaolin, the free-viscosity algorithm quantified the shear modulus of formed clots with a worst-case precision of 2.5%. Precision was improved to 1.8% by utilizing the fixed-viscosity algorithm. Repeated measurements showed a smooth evolution from liquid blood to a firm clot with a shear modulus between 1.4 kPa and 3.3 kPa. These results show the promise of this technique for rapid, point of care assessment of coagulation. PMID:26399992

Fast kinematic ray tracing of first- and later-arriving global seismic phases

NASA Astrophysics Data System (ADS)

Bijwaard, Harmen; Spakman, Wim

1999-11-01

We have developed a ray tracing algorithm that traces first- and later-arriving global seismic phases precisely (traveltime errors of the order of 0.1 s), and with great computational efficiency (15 rays s- 1). To achieve this, we have extended and adapted two existing ray tracing techniques: a graph method and a perturbation method. The two resulting algorithms are able to trace (critically) refracted, (multiply) reflected, some diffracted (Pdiff), and (multiply) converted seismic phases in a 3-D spherical geometry, thus including the largest part of seismic phases that are commonly observed on seismograms. We have tested and compared the two methods in 2-D and 3-D Cartesian and spherical models, for which both algorithms have yielded precise paths and traveltimes. These tests indicate that only the perturbation method is computationally efficient enough to perform 3-D ray tracing on global data sets of several million phases. To demonstrate its potential for non-linear tomography, we have applied the ray perturbation algorithm to a data set of 7.6 million P and pP phases used by Bijwaard et al. (1998) for linearized tomography. This showed that the expected heterogeneity within the Earth's mantle leads to significant non-linear effects on traveltimes for 10 per cent of the applied phases.

Determination of composition of non-homogeneous GaInNAs layers

NASA Astrophysics Data System (ADS)

Pucicki, D.; Bielak, K.; Ściana, B.; Radziewicz, D.; Latkowska-Baranowska, M.; Kováč, J.; Vincze, A.; Tłaczała, M.

2016-01-01

Dilute nitride GaInNAs alloys grown on GaAs have become perspective materials for so called low-cost GaAs-based devices working within the optical wavelength range up to 1.6 μm. The multilayer structures of GaInNAs/GaAs multi-quantum well (MQW) samples usually are analyzed by using high resolution X-ray diffraction (HRXRD) measurements. However, demands for precise structural characterization of the GaInNAs containing heterostructures requires taking into consideration all inhomogeneities of such structures. This paper describes some of the material challenges and progress in structural characterization of GaInNAs layers. A new algorithm for structural characterization of dilute nitrides which bounds contactless electro-reflectance (CER) or photo-reflectance (PR) measurements and HRXRD analysis results together with GaInNAs quantum well band diagram calculation is presented. The triple quantum well (3QW) GaInNAs/GaAs structures grown by atmospheric-pressure metalorganic vapor-phase epitaxy (AP-MOVPE) were investigated according to the proposed algorithm. Thanks to presented algorithm, more precise structural data including the nonuniformity in the growth direction of GaInNAs/GaAs QWs were achieved. Therefore, the proposed algorithm is mentioned as a nondestructive method for characterization of multicomponent inhomogeneous semiconductor structures with quantum wells.

Biased normalized cuts for target detection in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Xuewen; Dorado-Munoz, Leidy P.; Messinger, David W.; Cahill, Nathan D.

2016-05-01

The Biased Normalized Cuts (BNC) algorithm is a useful technique for detecting targets or objects in RGB imagery. In this paper, we propose modifying BNC for the purpose of target detection in hyperspectral imagery. As opposed to other target detection algorithms that typically encode target information prior to dimensionality reduction, our proposed algorithm encodes target information after dimensionality reduction, enabling a user to detect different targets in interactive mode. To assess the proposed BNC algorithm, we utilize hyperspectral imagery (HSI) from the SHARE 2012 data campaign, and we explore the relationship between the number and the position of expert-provided target labels and the precision/recall of the remaining targets in the scene.

Quantum-inspired algorithm for estimating the permanent of positive semidefinite matrices

NASA Astrophysics Data System (ADS)

Chakhmakhchyan, L.; Cerf, N. J.; Garcia-Patron, R.

2017-08-01

We construct a quantum-inspired classical algorithm for computing the permanent of Hermitian positive semidefinite matrices by exploiting a connection between these mathematical structures and the boson sampling model. Specifically, the permanent of a Hermitian positive semidefinite matrix can be expressed in terms of the expected value of a random variable, which stands for a specific photon-counting probability when measuring a linear-optically evolved random multimode coherent state. Our algorithm then approximates the matrix permanent from the corresponding sample mean and is shown to run in polynomial time for various sets of Hermitian positive semidefinite matrices, achieving a precision that improves over known techniques. This work illustrates how quantum optics may benefit algorithm development.

Validation of distal limb mounted inertial measurement unit sensors for stride detection in Warmblood horses at walk and trot.

PubMed

Bragança, F M; Bosch, S; Voskamp, J P; Marin-Perianu, M; Van der Zwaag, B J; Vernooij, J C M; van Weeren, P R; Back, W

2017-07-01

Inertial measurement unit (IMU) sensor-based techniques are becoming more popular in horses as a tool for objective locomotor assessment. To describe, evaluate and validate a method of stride detection and quantification at walk and trot using distal limb mounted IMU sensors. Prospective validation study comparing IMU sensors and motion capture with force plate data. A total of seven Warmblood horses equipped with metacarpal/metatarsal IMU sensors and reflective markers for motion capture were hand walked and trotted over a force plate. Using four custom built algorithms hoof-on/hoof-off timing over the force plate were calculated for each trial from the IMU data. Accuracy of the computed parameters was calculated as the mean difference in milliseconds between the IMU or motion capture generated data and the data from the force plate, precision as the s.d. of these differences and percentage of error with accuracy of the calculated parameter as a percentage of the force plate stance duration. Accuracy, precision and percentage of error of the best performing IMU algorithm for stance duration at walk were 28.5, 31.6 ms and 3.7% for the forelimbs and -5.5, 20.1 ms and -0.8% for the hindlimbs, respectively. At trot the best performing algorithm achieved accuracy, precision and percentage of error of -27.6/8.8 ms/-8.4% for the forelimbs and 6.3/33.5 ms/9.1% for the hindlimbs. The described algorithms have not been assessed on different surfaces. Inertial measurement unit technology can be used to determine temporal kinematic stride variables at walk and trot justifying its use in gait and performance analysis. However, precision of the method may not be sufficient to detect all possible lameness-related changes. These data seem promising enough to warrant further research to evaluate whether this approach will be useful for appraising the majority of clinically relevant gait changes encountered in practice. © 2016 The Authors. Equine Veterinary Journal published by John Wiley & Sons Ltd on behalf of EVJ Ltd.

Search for CP violation effects in the h→ τ τ decay with e^+e^- colliders

NASA Astrophysics Data System (ADS)

Chen, Xin; Wu, Yongcheng

2017-10-01

A new method is proposed to reconstruct the neutrinos in the e^+e^-→ Zh process followed by the h→ τ τ decay. With the help of a refined Higgs momentum reconstruction from the recoiling system and the impact parameters, high precision in the determination of the momentum of neutrinos can be achieved. The prospect of measuring the Higgs CP mixing angle with the h→ τ τ decay at e^+e^- colliders is studied with the new method. The analysis is based on a detailed detector simulation of the signal and backgrounds. The fully reconstructed neutrinos and also other visible products from the tau decay are used to build matrix element (ME)-based CP observables. With 5 ab^{-1} of data at E_{ {CM}}=250 GeV, a precision of 2.9° can be achieved for the CP mixing angle with three main one-prong decay modes of the taus. The precision is found to be about 35% better than the other methods.

Collaborative Localization and Location Verification in WSNs

PubMed Central

Miao, Chunyu; Dai, Guoyong; Ying, Kezhen; Chen, Qingzhang

2015-01-01

Localization is one of the most important technologies in wireless sensor networks. A lightweight distributed node localization scheme is proposed by considering the limited computational capacity of WSNs. The proposed scheme introduces the virtual force model to determine the location by incremental refinement. Aiming at solving the drifting problem and malicious anchor problem, a location verification algorithm based on the virtual force mode is presented. In addition, an anchor promotion algorithm using the localization reliability model is proposed to re-locate the drifted nodes. Extended simulation experiments indicate that the localization algorithm has relatively high precision and the location verification algorithm has relatively high accuracy. The communication overhead of these algorithms is relative low, and the whole set of reliable localization methods is practical as well as comprehensive. PMID:25954948

An Improved Image Matching Method Based on Surf Algorithm

NASA Astrophysics Data System (ADS)

Chen, S. J.; Zheng, S. Z.; Xu, Z. G.; Guo, C. C.; Ma, X. L.

2018-04-01

Many state-of-the-art image matching methods, based on the feature matching, have been widely studied in the remote sensing field. These methods of feature matching which get highly operating efficiency, have a disadvantage of low accuracy and robustness. This paper proposes an improved image matching method which based on the SURF algorithm. The proposed method introduces color invariant transformation, information entropy theory and a series of constraint conditions to increase feature points detection and matching accuracy. First, the model of color invariant transformation is introduced for two matching images aiming at obtaining more color information during the matching process and information entropy theory is used to obtain the most information of two matching images. Then SURF algorithm is applied to detect and describe points from the images. Finally, constraint conditions which including Delaunay triangulation construction, similarity function and projective invariant are employed to eliminate the mismatches so as to improve matching precision. The proposed method has been validated on the remote sensing images and the result benefits from its high precision and robustness.

Iterative methods for mixed finite element equations

NASA Technical Reports Server (NTRS)

Nakazawa, S.; Nagtegaal, J. C.; Zienkiewicz, O. C.

1985-01-01

Iterative strategies for the solution of indefinite system of equations arising from the mixed finite element method are investigated in this paper with application to linear and nonlinear problems in solid and structural mechanics. The augmented Hu-Washizu form is derived, which is then utilized to construct a family of iterative algorithms using the displacement method as the preconditioner. Two types of iterative algorithms are implemented. Those are: constant metric iterations which does not involve the update of preconditioner; variable metric iterations, in which the inverse of the preconditioning matrix is updated. A series of numerical experiments is conducted to evaluate the numerical performance with application to linear and nonlinear model problems.

Higher order temporal finite element methods through mixed formalisms.

PubMed

Kim, Jinkyu

2014-01-01

The extended framework of Hamilton's principle and the mixed convolved action principle provide new rigorous weak variational formalism for a broad range of initial boundary value problems in mathematical physics and mechanics. In this paper, their potential when adopting temporally higher order approximations is investigated. The classical single-degree-of-freedom dynamical systems are primarily considered to validate and to investigate the performance of the numerical algorithms developed from both formulations. For the undamped system, all the algorithms are symplectic and unconditionally stable with respect to the time step. For the damped system, they are shown to be accurate with good convergence characteristics.

A generalized interval fuzzy mixed integer programming model for a multimodal transportation problem under uncertainty

NASA Astrophysics Data System (ADS)

Tian, Wenli; Cao, Chengxuan

2017-03-01

A generalized interval fuzzy mixed integer programming model is proposed for the multimodal freight transportation problem under uncertainty, in which the optimal mode of transport and the optimal amount of each type of freight transported through each path need to be decided. For practical purposes, three mathematical methods, i.e. the interval ranking method, fuzzy linear programming method and linear weighted summation method, are applied to obtain equivalents of constraints and parameters, and then a fuzzy expected value model is presented. A heuristic algorithm based on a greedy criterion and the linear relaxation algorithm are designed to solve the model.

Mixed mode control method and engine using same

DOEpatents

Kesse, Mary L [Peoria, IL; Duffy, Kevin P [Metamora, IL

2007-04-10

A method of mixed mode operation of an internal combustion engine includes the steps of controlling a homogeneous charge combustion event timing in a given engine cycle, and controlling a conventional charge injection event to be at least a predetermined time after the homogeneous charge combustion event. An internal combustion engine is provided, including an electronic controller having a computer readable medium with a combustion timing control algorithm recorded thereon, the control algorithm including means for controlling a homogeneous charge combustion event timing and means for controlling a conventional injection event timing to be at least a predetermined time from the homogeneous charge combustion event.

Statistical Quality Control of Moisture Data in GEOS DAS

NASA Technical Reports Server (NTRS)

Dee, D. P.; Rukhovets, L.; Todling, R.

1999-01-01

A new statistical quality control algorithm was recently implemented in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The final step in the algorithm consists of an adaptive buddy check that either accepts or rejects outlier observations based on a local statistical analysis of nearby data. A basic assumption in any such test is that the observed field is spatially coherent, in the sense that nearby data can be expected to confirm each other. However, the buddy check resulted in excessive rejection of moisture data, especially during the Northern Hemisphere summer. The analysis moisture variable in GEOS DAS is water vapor mixing ratio. Observational evidence shows that the distribution of mixing ratio errors is far from normal. Furthermore, spatial correlations among mixing ratio errors are highly anisotropic and difficult to identify. Both factors contribute to the poor performance of the statistical quality control algorithm. To alleviate the problem, we applied the buddy check to relative humidity data instead. This variable explicitly depends on temperature and therefore exhibits a much greater spatial coherence. As a result, reject rates of moisture data are much more reasonable and homogeneous in time and space.

[Preliminary application of an improved Demons deformable registration algorithm in tumor radiotherapy].

PubMed

Zhou, Lu; Zhen, Xin; Lu, Wenting; Dou, Jianhong; Zhou, Linghong

2012-01-01

To validate the efficiency of an improved Demons deformable registration algorithm and evaluate its application in registration of the treatment image and the planning image in image-guided radiotherapy (IGRT). Based on Brox's gradient constancy assumption and Malis's efficient second-order minimization algorithm, a grey value gradient similarity term was added into the original energy function, and a formula was derived to calculate the update of transformation field. The limited Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm was used to optimize the energy function for automatic determination of the iteration number. The proposed algorithm was validated using mathematically deformed images, physically deformed phantom images and clinical tumor images. Compared with the original Additive Demons algorithm, the improved Demons algorithm achieved a higher precision and a faster convergence speed. Due to the influence of different scanning conditions in fractionated radiation, the density range of the treatment image and the planning image may be different. The improved Demons algorithm can achieve faster and more accurate radiotherapy.

Clustering PPI data by combining FA and SHC method.

PubMed

Lei, Xiujuan; Ying, Chao; Wu, Fang-Xiang; Xu, Jin

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value.

Clustering PPI data by combining FA and SHC method

PubMed Central

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value. PMID:25707632

A Discussion of Using a Reconfigurable Processor to Implement the Discrete Fourier Transform

NASA Technical Reports Server (NTRS)

White, Michael J.

2004-01-01

This paper presents the design and implementation of the Discrete Fourier Transform (DFT) algorithm on a reconfigurable processor system. While highly applicable to many engineering problems, the DFT is an extremely computationally intensive algorithm. Consequently, the eventual goal of this work is to enhance the execution of a floating-point precision DFT algorithm by off loading the algorithm from the computing system. This computing system, within the context of this research, is a typical high performance desktop computer with an may of field programmable gate arrays (FPGAs). FPGAs are hardware devices that are configured by software to execute an algorithm. If it is desired to change the algorithm, the software is changed to reflect the modification, then download to the FPGA, which is then itself modified. This paper will discuss methodology for developing the DFT algorithm to be implemented on the FPGA. We will discuss the algorithm, the FPGA code effort, and the results to date.

Multi-Target Angle Tracking Algorithm for Bistatic MIMO Radar Based on the Elements of the Covariance Matrix

PubMed Central

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-01-01

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar. PMID:29518957

Multi-Target Angle Tracking Algorithm for Bistatic Multiple-Input Multiple-Output (MIMO) Radar Based on the Elements of the Covariance Matrix.

PubMed

Zhang, Zhengyan; Zhang, Jianyun; Zhou, Qingsong; Li, Xiaobo

2018-03-07

In this paper, we consider the problem of tracking the direction of arrivals (DOA) and the direction of departure (DOD) of multiple targets for bistatic multiple-input multiple-output (MIMO) radar. A high-precision tracking algorithm for target angle is proposed. First, the linear relationship between the covariance matrix difference and the angle difference of the adjacent moment was obtained through three approximate relations. Then, the proposed algorithm obtained the relationship between the elements in the covariance matrix difference. On this basis, the performance of the algorithm was improved by averaging the covariance matrix element. Finally, the least square method was used to estimate the DOD and DOA. The algorithm realized the automatic correlation of the angle and provided better performance when compared with the adaptive asymmetric joint diagonalization (AAJD) algorithm. The simulation results demonstrated the effectiveness of the proposed algorithm. The algorithm provides the technical support for the practical application of MIMO radar.

A novel complex networks clustering algorithm based on the core influence of nodes.

PubMed

Tong, Chao; Niu, Jianwei; Dai, Bin; Xie, Zhongyu

2014-01-01

In complex networks, cluster structure, identified by the heterogeneity of nodes, has become a common and important topological property. Network clustering methods are thus significant for the study of complex networks. Currently, many typical clustering algorithms have some weakness like inaccuracy and slow convergence. In this paper, we propose a clustering algorithm by calculating the core influence of nodes. The clustering process is a simulation of the process of cluster formation in sociology. The algorithm detects the nodes with core influence through their betweenness centrality, and builds the cluster's core structure by discriminant functions. Next, the algorithm gets the final cluster structure after clustering the rest of the nodes in the network by optimizing method. Experiments on different datasets show that the clustering accuracy of this algorithm is superior to the classical clustering algorithm (Fast-Newman algorithm). It clusters faster and plays a positive role in revealing the real cluster structure of complex networks precisely.

Fully-coupled analysis of jet mixing problems. Three-dimensional PNS model, SCIP3D

NASA Technical Reports Server (NTRS)

Wolf, D. E.; Sinha, N.; Dash, S. M.

1988-01-01

Numerical procedures formulated for the analysis of 3D jet mixing problems, as incorporated in the computer model, SCIP3D, are described. The overall methodology closely parallels that developed in the earlier 2D axisymmetric jet mixing model, SCIPVIS. SCIP3D integrates the 3D parabolized Navier-Stokes (PNS) jet mixing equations, cast in mapped cartesian or cylindrical coordinates, employing the explicit MacCormack Algorithm. A pressure split variant of this algorithm is employed in subsonic regions with a sublayer approximation utilized for treating the streamwise pressure component. SCIP3D contains both the ks and kW turbulence models, and employs a two component mixture approach to treat jet exhausts of arbitrary composition. Specialized grid procedures are used to adjust the grid growth in accordance with the growth of the jet, including a hybrid cartesian/cylindrical grid procedure for rectangular jets which moves the hybrid coordinate origin towards the flow origin as the jet transitions from a rectangular to circular shape. Numerous calculations are presented for rectangular mixing problems, as well as for a variety of basic unit problems exhibiting overall capabilities of SCIP3D.

High-precision measurement of chlorine stable isotope ratios

USGS Publications Warehouse

Long, A.; Eastoe, C.J.; Kaufmann, R.S.; Martin, J.G.; Wirt, L.; Finley, J.B.

1993-01-01

We present an analysis procedure that allows stable isotopes of chlorine to be analyzed with precision sufficient for geological and hydrological studies. The total analytical precision is ?????0.09%., and the present known range of chloride in the surface and near-surface environment is 3.5???. As Cl- is essentially nonreactive in natural aquatic environments, it is a conservative tracer and its ??37Cl is also conservative. Thus, the ??37Cl parameter is valuable for quantitative evaluation of mixing of different sources of chloride in brines and aquifers. ?? 1993.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grout, Ray W. S.

Convergence of spectral deferred correction (SDC), where low-order time integration methods are used to construct higher-order methods through iterative refinement, can be accelerated in terms of computational effort by using mixed-precision methods. Using ideas from multi-level SDC (in turn based on FAS multigrid ideas), some of the SDC correction sweeps can use function values computed in reduced precision without adversely impacting the accuracy of the final solution. This is particularly beneficial for the performance of combustion solvers such as S3D [6] which require double precision accuracy but are performance limited by the cost of data motion.

A Raman chemical imaging system for detection of contaminants in food

NASA Astrophysics Data System (ADS)

Chao, Kaunglin; Qin, Jianwei; Kim, Moon S.; Mo, Chang Yeon

2011-06-01

This study presented a preliminary investigation into the use of macro-scale Raman chemical imaging for the screening of dry milk powder for the presence of chemical contaminants. Melamine was mixed into dry milk at concentrations (w/w) of 0.2%, 0.5%, 1.0%, 2.0%, 5.0%, and 10.0% and images of the mixtures were analyzed by a spectral information divergence algorithm. Ammonium sulfate, dicyandiamide, and urea were each separately mixed into dry milk at concentrations of (w/w) of 0.5%, 1.0%, and 5.0%, and an algorithm based on self-modeling mixture analysis was applied to these sample images. The contaminants were successfully detected and the spatial distribution of the contaminants within the sample mixtures was visualized using these algorithms. Although further studies are necessary, macro-scale Raman chemical imaging shows promise for use in detecting contaminants in food ingredients and may also be useful for authentication of food ingredients.

Mixing geometric and radiometric features for change classification

NASA Astrophysics Data System (ADS)

Fournier, Alexandre; Descombes, Xavier; Zerubia, Josiane

2008-02-01

Most basic change detection algorithms use a pixel-based approach. Whereas such approach is quite well defined for monitoring important area changes (such as urban growth monitoring) in low resolution images, an object based approach seems more relevant when the change detection is specifically aimed toward targets (such as small buildings and vehicles). In this paper, we present an approach that mixes radiometric and geometric features to qualify the changed zones. The goal is to establish bounds (appearance, disappearance, substitution ...) between the detected changes and the underlying objects. We proceed by first clustering the change map (containing each pixel bitemporal radiosity) in different classes using the entropy-kmeans algorithm. Assuming that most man-made objects have a polygonal shape, a polygonal approximation algorithm is then used in order to characterize the resulting zone shapes. Hence allowing us to refine the primary rough classification, by integrating the polygon orientations in the state space. Tests are currently conducted on Quickbird data.

Dilution of Precision as a Geometry Metric for Swarm Relative Localization

DTIC Science & Technology

2017-11-01

algorithm 2.2 Intuitive DOP Illustration Before proceeding with a quantitative definition of DOP, an intuitive example will be given to illustrate the...in Fig. 11 4.2.2 Constant DOP Example Compare the results of the previous simulation to those shown in Figs. 13 and 14. Instead of only scaling...ARL-TR-8200 ● NOV 2017 US Army Research Laboratory Dilution of Precision as a Geometry Metric for Swarm Relative Localization

Taxamatch, an Algorithm for Near (‘Fuzzy’) Matching of Scientific Names in Taxonomic Databases

PubMed Central

Rees, Tony

2014-01-01

Misspellings of organism scientific names create barriers to optimal storage and organization of biological data, reconciliation of data stored under different spelling variants of the same name, and appropriate responses from user queries to taxonomic data systems. This study presents an analysis of the nature of the problem from first principles, reviews some available algorithmic approaches, and describes Taxamatch, an improved name matching solution for this information domain. Taxamatch employs a custom Modified Damerau-Levenshtein Distance algorithm in tandem with a phonetic algorithm, together with a rule-based approach incorporating a suite of heuristic filters, to produce improved levels of recall, precision and execution time over the existing dynamic programming algorithms n-grams (as bigrams and trigrams) and standard edit distance. Although entirely phonetic methods are faster than Taxamatch, they are inferior in the area of recall since many real-world errors are non-phonetic in nature. Excellent performance of Taxamatch (as recall, precision and execution time) is demonstrated against a reference database of over 465,000 genus names and 1.6 million species names, as well as against a range of error types as present at both genus and species levels in three sets of sample data for species and four for genera alone. An ancillary authority matching component is included which can be used both for misspelled names and for otherwise matching names where the associated cited authorities are not identical. PMID:25247892

A modern control theory based algorithm for control of the NASA/JPL 70-meter antenna axis servos

NASA Technical Reports Server (NTRS)

Hill, R. E.

1987-01-01

A digital computer-based state variable controller was designed and applied to the 70-m antenna axis servos. The general equations and structure of the algorithm and provisions for alternate position error feedback modes to accommodate intertarget slew, encoder referenced tracking, and precision tracking modes are descibed. Development of the discrete time domain control model and computation of estimator and control gain parameters based on closed loop pole placement criteria are discussed. The new algorithm was successfully implemented and tested in the 70-m antenna at Deep Space Network station 63 in Spain.

An atlas of Rapp's 180-th order geopotential.

NASA Astrophysics Data System (ADS)

Melvin, P. J.

1986-08-01

Deprit's 1979 approach to the summation of the spherical harmonic expansion of the geopotential has been modified to spherical components and normalized Legendre polynomials. An algorithm has been developed which produces ten fields at the users option: the undulations of the geoid, three anomalous components of the gravity vector, or six components of the Hessian of the geopotential (gravity gradient). The algorithm is stable to high orders in single precision and does not treat the polar regions as a special case. Eleven contour maps of components of the anomalous geopotential on the surface of the ellipsoid are presented to validate the algorithm.

Comparative analysis of algorithms for lunar landing control

NASA Astrophysics Data System (ADS)

Zhukov, B. I.; Likhachev, V. N.; Sazonov, V. V.; Sikharulidze, Yu. G.; Tuchin, A. G.; Tuchin, D. A.; Fedotov, V. P.; Yaroshevskii, V. S.

2015-11-01

For the descent from the pericenter of a prelanding circumlunar orbit a comparison of three algorithms for the control of lander motion is performed. These algorithms use various combinations of terminal and programmed control in a trajectory including three parts: main braking, precision braking, and descent with constant velocity. In the first approximation, autonomous navigational measurements are taken into account and an estimate of the disturbances generated by movement of the fuel in the tanks was obtained. Estimates of the accuracy for landing placement, fuel consumption, and performance of the conditions for safe lunar landing are obtained.

Computing interior eigenvalues of nonsymmetric matrices: application to three-dimensional metamaterial composites.

PubMed

Terao, Takamichi

2010-08-01

We propose a numerical method to calculate interior eigenvalues and corresponding eigenvectors for nonsymmetric matrices. Based on the subspace projection technique onto expanded Ritz subspace, it becomes possible to obtain eigenvalues and eigenvectors with sufficiently high precision. This method overcomes the difficulties of the traditional nonsymmetric Lanczos algorithm, and improves the accuracy of the obtained interior eigenvalues and eigenvectors. Using this algorithm, we investigate three-dimensional metamaterial composites consisting of positive and negative refractive index materials, and it is demonstrated that the finite-difference frequency-domain algorithm is applicable to analyze these metamaterial composites.

CHAMP: a locally adaptive unmixing-based hyperspectral anomaly detection algorithm

NASA Astrophysics Data System (ADS)

Crist, Eric P.; Thelen, Brian J.; Carrara, David A.

1998-10-01

Anomaly detection offers a means by which to identify potentially important objects in a scene without prior knowledge of their spectral signatures. As such, this approach is less sensitive to variations in target class composition, atmospheric and illumination conditions, and sensor gain settings than would be a spectral matched filter or similar algorithm. The best existing anomaly detectors generally fall into one of two categories: those based on local Gaussian statistics, and those based on linear mixing moles. Unmixing-based approaches better represent the real distribution of data in a scene, but are typically derived and applied on a global or scene-wide basis. Locally adaptive approaches allow detection of more subtle anomalies by accommodating the spatial non-homogeneity of background classes in a typical scene, but provide a poorer representation of the true underlying background distribution. The CHAMP algorithm combines the best attributes of both approaches, applying a linear-mixing model approach in a spatially adaptive manner. The algorithm itself, and teste results on simulated and actual hyperspectral image data, are presented in this paper.

Preconditioned Mixed Spectral Element Methods for Elasticity and Stokes Problems

NASA Technical Reports Server (NTRS)

Pavarino, Luca F.

1996-01-01

Preconditioned iterative methods for the indefinite systems obtained by discretizing the linear elasticity and Stokes problems with mixed spectral elements in three dimensions are introduced and analyzed. The resulting stiffness matrices have the structure of saddle point problems with a penalty term, which is associated with the Poisson ratio for elasticity problems or with stabilization techniques for Stokes problems. The main results of this paper show that the convergence rate of the resulting algorithms is independent of the penalty parameter, the number of spectral elements Nu and mildly dependent on the spectral degree eta via the inf-sup constant. The preconditioners proposed for the whole indefinite system are block-diagonal and block-triangular. Numerical experiments presented in the final section show that these algorithms are a practical and efficient strategy for the iterative solution of the indefinite problems arising from mixed spectral element discretizations of elliptic systems.

An Optimal Order Nonnested Mixed Multigrid Method for Generalized Stokes Problems

NASA Technical Reports Server (NTRS)

Deng, Qingping

1996-01-01

A multigrid algorithm is developed and analyzed for generalized Stokes problems discretized by various nonnested mixed finite elements within a unified framework. It is abstractly proved by an element-independent analysis that the multigrid algorithm converges with an optimal order if there exists a 'good' prolongation operator. A technique to construct a 'good' prolongation operator for nonnested multilevel finite element spaces is proposed. Its basic idea is to introduce a sequence of auxiliary nested multilevel finite element spaces and define a prolongation operator as a composite operator of two single grid level operators. This makes not only the construction of a prolongation operator much easier (the final explicit forms of such prolongation operators are fairly simple), but the verification of the approximate properties for prolongation operators is also simplified. Finally, as an application, the framework and technique is applied to seven typical nonnested mixed finite elements.